W2.ipynb

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   "source": [
    "# Introduction to Libraries in Python\n",
    "Python is renowned for its extensive collection of libraries that extend its capabilities beyond the basic functions of the language. These libraries are precompiled codes, which can be used in various programs for specific operations, saving time and effort for developers. <br>\n",
    "## What is a Library?\n",
    "In the context of programming, a library is akin to a collection of books in a traditional library. It’s a set of pre-written code modules that serve a specific functionality. These modules are reusable and can be integrated into a programmer’s code, enhancing the development process and functionality of the software. <br>\n",
    "## Python Standard Library\n",
    "The Python Standard Library is a powerful toolkit included with every Python installation. It contains <ins>over 200</ins> core modules that provide access to system functionality and are essential for programming tasks ranging from file I/O to data serialization. <br>\n",
    "## Popular Python Libraries\n",
    "Here are some of the most popular Python libraries that have become staples in various domains:<br>\n",
    "\n",
    "* ### Matplotlib\n",
    "A plotting library for creating static, interactive, and animated visualizations in Python. It’s highly useful for data visualization and graphical plotting.\n",
    "\n",
    "* ### NumPy:\n",
    "A library for numerical computing, providing support for large, multi-dimensional arrays and matrices, along with a collection of mathematical functions to operate on these arrays\n",
    "\n",
    "* ### Pandas:\n",
    "An open-source library providing high-performance, easy-to-use data structures, and data analysis tools. It’s particularly well-suited for structured data operations and manipulations.\n",
    "\n",
    "* ### OSGeo:\n",
    "`OSGeo`, the Open Source Geospatial Foundation, supports and promotes the collaborative development of open geospatial technologies and data. The OSGeo library in Python is a collection of tools for processing geospatial data, supporting the likes of GDAL/OGR, Proj.4, GEOS, etc\n",
    "\n",
    "* ### Seaborn:\n",
    "`Seaborn` is a statistical data visualization library in Python. It’s based on matplotlib and provides a high-level interface for drawing attractive and informative statistical graphics\n",
    "\n",
    "* ### Scikit-learn\n",
    "\n",
    "`Scikit-learn` is a powerful Python library for machine learning. It provides simple and efficient tools for data mining and data analysis. It’s built on `NumPy`, `SciPy`, and `matplotlib`, and it’s open source, commercially usable - BSD licensed:\n",
    "\n",
    "* ### TensorFlow:\n",
    "Developed by **Google**, this open-source library is used for high-level computations and is instrumental in machine learning and deep learning algorithms\n",
    "\n",
    "* ### Xarray:\n",
    "`Xarray` is an open-source project and Python library that makes working with labelled multi-dimensional arrays simple, efficient, and fun! Xarray introduces labels in the form of dimensions, coordinates, and attributes on top of raw NumPy-like arrays, which makes data more self-describing and interoperable\n",
    "\n"
   ]
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   "source": [
    "# Using pip to Install Python Libraries\n",
    "\n",
    "`pip` is the library installer for Python. You can use it to install Libraries from the Python library Index (PyPI) and other indexes.\n",
    "\n",
    "## How to Install a Libraries with pip\n",
    "\n",
    "To install a library, open your command-line interface and enter:\n",
    "\n",
    "```bash\n",
    "pip install package-name\n"
   ]
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  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3941c489-10a3-424d-bdd2-33445ac8b4aa",
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     "text": [
      "Requirement already satisfied: xarray in /usr/local/lib/python3.10/dist-packages (2023.7.0)\n",
      "Requirement already satisfied: numpy>=1.21 in /usr/local/lib/python3.10/dist-packages (from xarray) (1.25.2)\n",
      "Requirement already satisfied: pandas>=1.4 in /usr/local/lib/python3.10/dist-packages (from xarray) (2.0.3)\n",
      "Requirement already satisfied: packaging>=21.3 in /usr/local/lib/python3.10/dist-packages (from xarray) (24.0)\n",
      "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from pandas>=1.4->xarray) (2.8.2)\n",
      "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=1.4->xarray) (2023.4)\n",
      "Requirement already satisfied: tzdata>=2022.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=1.4->xarray) (2024.1)\n",
      "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.2->pandas>=1.4->xarray) (1.16.0)\n"
     ]
    }
   ],
   "source": [
    "pip install xarray"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b4631373",
   "metadata": {
    "id": "b4631373"
   },
   "source": [
    "## How to List Installed Python Packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e321429a",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
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    "id": "e321429a",
    "outputId": "b4fddb23-8fb8-4cbe-9766-e3dd3cbe5ec6"
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    {
     "name": "stdout",
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     "text": [
      "Package                          Version\n",
      "-------------------------------- ---------------------\n",
      "absl-py                          1.4.0\n",
      "aiohttp                          3.9.5\n",
      "aiosignal                        1.3.1\n",
      "alabaster                        0.7.16\n",
      "albumentations                   1.3.1\n",
      "altair                           4.2.2\n",
      "annotated-types                  0.6.0\n",
      "anyio                            3.7.1\n",
      "appdirs                          1.4.4\n",
      "argon2-cffi                      23.1.0\n",
      "argon2-cffi-bindings             21.2.0\n",
      "array_record                     0.5.1\n",
      "arviz                            0.15.1\n",
      "astropy                          5.3.4\n",
      "astunparse                       1.6.3\n",
      "async-timeout                    4.0.3\n",
      "atpublic                         4.1.0\n",
      "attrs                            23.2.0\n",
      "audioread                        3.0.1\n",
      "autograd                         1.6.2\n",
      "Babel                            2.14.0\n",
      "backcall                         0.2.0\n",
      "beautifulsoup4                   4.12.3\n",
      "bidict                           0.23.1\n",
      "bigframes                        1.4.0\n",
      "bleach                           6.1.0\n",
      "blinker                          1.4\n",
      "blis                             0.7.11\n",
      "blosc2                           2.0.0\n",
      "bokeh                            3.3.4\n",
      "bqplot                           0.12.43\n",
      "branca                           0.7.2\n",
      "build                            1.2.1\n",
      "CacheControl                     0.14.0\n",
      "cachetools                       5.3.3\n",
      "catalogue                        2.0.10\n",
      "certifi                          2024.2.2\n",
      "cffi                             1.16.0\n",
      "chardet                          5.2.0\n",
      "charset-normalizer               3.3.2\n",
      "chex                             0.1.86\n",
      "click                            8.1.7\n",
      "click-plugins                    1.1.1\n",
      "cligj                            0.7.2\n",
      "cloudpathlib                     0.16.0\n",
      "cloudpickle                      2.2.1\n",
      "cmake                            3.27.9\n",
      "cmdstanpy                        1.2.2\n",
      "colorcet                         3.1.0\n",
      "colorlover                       0.3.0\n",
      "colour                           0.1.5\n",
      "community                        1.0.0b1\n",
      "confection                       0.1.4\n",
      "cons                             0.4.6\n",
      "contextlib2                      21.6.0\n",
      "contourpy                        1.2.1\n",
      "cryptography                     42.0.5\n",
      "cufflinks                        0.17.3\n",
      "cupy-cuda12x                     12.2.0\n",
      "cvxopt                           1.3.2\n",
      "cvxpy                            1.3.4\n",
      "cycler                           0.12.1\n",
      "cymem                            2.0.8\n",
      "Cython                           3.0.10\n",
      "dask                             2023.8.1\n",
      "datascience                      0.17.6\n",
      "db-dtypes                        1.2.0\n",
      "dbus-python                      1.2.18\n",
      "debugpy                          1.6.6\n",
      "decorator                        4.4.2\n",
      "defusedxml                       0.7.1\n",
      "distributed                      2023.8.1\n",
      "distro                           1.7.0\n",
      "dlib                             19.24.4\n",
      "dm-tree                          0.1.8\n",
      "docstring_parser                 0.16\n",
      "docutils                         0.18.1\n",
      "dopamine-rl                      4.0.6\n",
      "duckdb                           0.10.2\n",
      "earthengine-api                  0.1.400\n",
      "easydict                         1.13\n",
      "ecos                             2.0.13\n",
      "editdistance                     0.6.2\n",
      "eerepr                           0.0.4\n",
      "en-core-web-sm                   3.7.1\n",
      "entrypoints                      0.4\n",
      "et-xmlfile                       1.1.0\n",
      "etils                            1.7.0\n",
      "etuples                          0.3.9\n",
      "exceptiongroup                   1.2.1\n",
      "fastai                           2.7.15\n",
      "fastcore                         1.5.33\n",
      "fastdownload                     0.0.7\n",
      "fastjsonschema                   2.19.1\n",
      "fastprogress                     1.0.3\n",
      "fastrlock                        0.8.2\n",
      "filelock                         3.14.0\n",
      "fiona                            1.9.6\n",
      "firebase-admin                   5.3.0\n",
      "Flask                            2.2.5\n",
      "flatbuffers                      24.3.25\n",
      "flax                             0.8.3\n",
      "folium                           0.14.0\n",
      "fonttools                        4.51.0\n",
      "frozendict                       2.4.2\n",
      "frozenlist                       1.4.1\n",
      "fsspec                           2023.6.0\n",
      "future                           0.18.3\n",
      "gast                             0.5.4\n",
      "gcsfs                            2023.6.0\n",
      "GDAL                             3.6.4\n",
      "gdown                            5.1.0\n",
      "geemap                           0.32.0\n",
      "gensim                           4.3.2\n",
      "geocoder                         1.38.1\n",
      "geographiclib                    2.0\n",
      "geopandas                        0.13.2\n",
      "geopy                            2.3.0\n",
      "gin-config                       0.5.0\n",
      "glob2                            0.7\n",
      "google                           2.0.3\n",
      "google-ai-generativelanguage     0.6.2\n",
      "google-api-core                  2.11.1\n",
      "google-api-python-client         2.84.0\n",
      "google-auth                      2.27.0\n",
      "google-auth-httplib2             0.1.1\n",
      "google-auth-oauthlib             1.2.0\n",
      "google-cloud-aiplatform          1.48.0\n",
      "google-cloud-bigquery            3.21.0\n",
      "google-cloud-bigquery-connection 1.12.1\n",
      "google-cloud-bigquery-storage    2.24.0\n",
      "google-cloud-core                2.3.3\n",
      "google-cloud-datastore           2.15.2\n",
      "google-cloud-firestore           2.11.1\n",
      "google-cloud-functions           1.13.3\n",
      "google-cloud-iam                 2.15.0\n",
      "google-cloud-language            2.13.3\n",
      "google-cloud-resource-manager    1.12.3\n",
      "google-cloud-storage             2.8.0\n",
      "google-cloud-translate           3.11.3\n",
      "google-colab                     1.0.0\n",
      "google-crc32c                    1.5.0\n",
      "google-generativeai              0.5.2\n",
      "google-pasta                     0.2.0\n",
      "google-resumable-media           2.7.0\n",
      "googleapis-common-protos         1.63.0\n",
      "googledrivedownloader            0.4\n",
      "graphviz                         0.20.3\n",
      "greenlet                         3.0.3\n",
      "grpc-google-iam-v1               0.13.0\n",
      "grpcio                           1.63.0\n",
      "grpcio-status                    1.48.2\n",
      "gspread                          6.0.2\n",
      "gspread-dataframe                3.3.1\n",
      "gym                              0.25.2\n",
      "gym-notices                      0.0.8\n",
      "h5netcdf                         1.3.0\n",
      "h5py                             3.9.0\n",
      "holidays                         0.47\n",
      "holoviews                        1.17.1\n",
      "html5lib                         1.1\n",
      "httpimport                       1.3.1\n",
      "httplib2                         0.22.0\n",
      "huggingface-hub                  0.20.3\n",
      "humanize                         4.7.0\n",
      "hyperopt                         0.2.7\n",
      "ibis-framework                   8.0.0\n",
      "idna                             3.7\n",
      "imageio                          2.31.6\n",
      "imageio-ffmpeg                   0.4.9\n",
      "imagesize                        1.4.1\n",
      "imbalanced-learn                 0.10.1\n",
      "imgaug                           0.4.0\n",
      "importlib_metadata               7.1.0\n",
      "importlib_resources              6.4.0\n",
      "imutils                          0.5.4\n",
      "inflect                          7.0.0\n",
      "iniconfig                        2.0.0\n",
      "intel-openmp                     2023.2.4\n",
      "ipyevents                        2.0.2\n",
      "ipyfilechooser                   0.6.0\n",
      "ipykernel                        5.5.6\n",
      "ipyleaflet                       0.18.2\n",
      "ipython                          7.34.0\n",
      "ipython-genutils                 0.2.0\n",
      "ipython-sql                      0.5.0\n",
      "ipytree                          0.2.2\n",
      "ipywidgets                       7.7.1\n",
      "itsdangerous                     2.2.0\n",
      "jax                              0.4.26\n",
      "jaxlib                           0.4.26+cuda12.cudnn89\n",
      "jeepney                          0.7.1\n",
      "jieba                            0.42.1\n",
      "Jinja2                           3.1.3\n",
      "joblib                           1.4.0\n",
      "jsonpickle                       3.0.4\n",
      "jsonschema                       4.19.2\n",
      "jsonschema-specifications        2023.12.1\n",
      "jupyter-client                   6.1.12\n",
      "jupyter-console                  6.1.0\n",
      "jupyter_core                     5.7.2\n",
      "jupyter-server                   1.24.0\n",
      "jupyterlab_pygments              0.3.0\n",
      "jupyterlab_widgets               3.0.10\n",
      "kaggle                           1.6.12\n",
      "kagglehub                        0.2.4\n",
      "keras                            2.15.0\n",
      "keyring                          23.5.0\n",
      "kiwisolver                       1.4.5\n",
      "langcodes                        3.4.0\n",
      "language_data                    1.2.0\n",
      "launchpadlib                     1.10.16\n",
      "lazr.restfulclient               0.14.4\n",
      "lazr.uri                         1.0.6\n",
      "lazy_loader                      0.4\n",
      "libclang                         18.1.1\n",
      "librosa                          0.10.1\n",
      "lightgbm                         4.1.0\n",
      "linkify-it-py                    2.0.3\n",
      "llvmlite                         0.41.1\n",
      "locket                           1.0.0\n",
      "logical-unification              0.4.6\n",
      "lxml                             4.9.4\n",
      "malloy                           2023.1067\n",
      "marisa-trie                      1.1.0\n",
      "Markdown                         3.6\n",
      "markdown-it-py                   3.0.0\n",
      "MarkupSafe                       2.1.5\n",
      "matplotlib                       3.7.1\n",
      "matplotlib-inline                0.1.7\n",
      "matplotlib-venn                  0.11.10\n",
      "mdit-py-plugins                  0.4.0\n",
      "mdurl                            0.1.2\n",
      "miniKanren                       1.0.3\n",
      "missingno                        0.5.2\n",
      "mistune                          0.8.4\n",
      "mizani                           0.9.3\n",
      "mkl                              2023.2.0\n",
      "ml-dtypes                        0.2.0\n",
      "mlxtend                          0.22.0\n",
      "more-itertools                   10.1.0\n",
      "moviepy                          1.0.3\n",
      "mpmath                           1.3.0\n",
      "msgpack                          1.0.8\n",
      "multidict                        6.0.5\n",
      "multipledispatch                 1.0.0\n",
      "multitasking                     0.0.11\n",
      "murmurhash                       1.0.10\n",
      "music21                          9.1.0\n",
      "natsort                          8.4.0\n",
      "nbclassic                        1.0.0\n",
      "nbclient                         0.10.0\n",
      "nbconvert                        6.5.4\n",
      "nbformat                         5.10.4\n",
      "nest-asyncio                     1.6.0\n",
      "networkx                         3.3\n",
      "nibabel                          4.0.2\n",
      "nltk                             3.8.1\n",
      "notebook                         6.5.5\n",
      "notebook_shim                    0.2.4\n",
      "numba                            0.58.1\n",
      "numexpr                          2.10.0\n",
      "numpy                            1.25.2\n",
      "oauth2client                     4.1.3\n",
      "oauthlib                         3.2.2\n",
      "opencv-contrib-python            4.8.0.76\n",
      "opencv-python                    4.8.0.76\n",
      "opencv-python-headless           4.9.0.80\n",
      "openpyxl                         3.1.2\n",
      "opt-einsum                       3.3.0\n",
      "optax                            0.2.2\n",
      "orbax-checkpoint                 0.4.4\n",
      "osqp                             0.6.2.post8\n",
      "packaging                        24.0\n",
      "pandas                           2.0.3\n",
      "pandas-datareader                0.10.0\n",
      "pandas-gbq                       0.19.2\n",
      "pandas-stubs                     2.0.3.230814\n",
      "pandocfilters                    1.5.1\n",
      "panel                            1.3.8\n",
      "param                            2.1.0\n",
      "parso                            0.8.4\n",
      "parsy                            2.1\n",
      "partd                            1.4.1\n",
      "pathlib                          1.0.1\n",
      "patsy                            0.5.6\n",
      "peewee                           3.17.3\n",
      "pexpect                          4.9.0\n",
      "pickleshare                      0.7.5\n",
      "Pillow                           9.4.0\n",
      "pip                              23.1.2\n",
      "pip-tools                        6.13.0\n",
      "platformdirs                     4.2.1\n",
      "plotly                           5.15.0\n",
      "plotnine                         0.12.4\n",
      "pluggy                           1.5.0\n",
      "polars                           0.20.2\n",
      "pooch                            1.8.1\n",
      "portpicker                       1.5.2\n",
      "prefetch-generator               1.0.3\n",
      "preshed                          3.0.9\n",
      "prettytable                      3.10.0\n",
      "proglog                          0.1.10\n",
      "progressbar2                     4.2.0\n",
      "prometheus_client                0.20.0\n",
      "promise                          2.3\n",
      "prompt-toolkit                   3.0.43\n",
      "prophet                          1.1.5\n",
      "proto-plus                       1.23.0\n",
      "protobuf                         3.20.3\n",
      "psutil                           5.9.5\n",
      "psycopg2                         2.9.9\n",
      "ptyprocess                       0.7.0\n",
      "py-cpuinfo                       9.0.0\n",
      "py4j                             0.10.9.7\n",
      "pyarrow                          14.0.2\n",
      "pyarrow-hotfix                   0.6\n",
      "pyasn1                           0.6.0\n",
      "pyasn1_modules                   0.4.0\n",
      "pycocotools                      2.0.7\n",
      "pycparser                        2.22\n",
      "pydantic                         2.7.1\n",
      "pydantic_core                    2.18.2\n",
      "pydata-google-auth               1.8.2\n",
      "pydot                            1.4.2\n",
      "pydot-ng                         2.0.0\n",
      "pydotplus                        2.0.2\n",
      "PyDrive                          1.3.1\n",
      "PyDrive2                         1.6.3\n",
      "pyerfa                           2.0.1.4\n",
      "pygame                           2.5.2\n",
      "Pygments                         2.16.1\n",
      "PyGObject                        3.42.1\n",
      "PyJWT                            2.3.0\n",
      "pymc                             5.10.4\n",
      "pymystem3                        0.2.0\n",
      "PyOpenGL                         3.1.7\n",
      "pyOpenSSL                        24.1.0\n",
      "pyparsing                        3.1.2\n",
      "pyperclip                        1.8.2\n",
      "pyproj                           3.6.1\n",
      "pyproject_hooks                  1.1.0\n",
      "pyshp                            2.3.1\n",
      "PySocks                          1.7.1\n",
      "pytensor                         2.18.6\n",
      "pytest                           7.4.4\n",
      "python-apt                       0.0.0\n",
      "python-box                       7.1.1\n",
      "python-dateutil                  2.8.2\n",
      "python-louvain                   0.16\n",
      "python-slugify                   8.0.4\n",
      "python-utils                     3.8.2\n",
      "pytz                             2023.4\n",
      "pyviz_comms                      3.0.2\n",
      "PyWavelets                       1.6.0\n",
      "PyYAML                           6.0.1\n",
      "pyzmq                            24.0.1\n",
      "qdldl                            0.1.7.post2\n",
      "qudida                           0.0.4\n",
      "ratelim                          0.1.6\n",
      "referencing                      0.35.0\n",
      "regex                            2023.12.25\n",
      "requests                         2.31.0\n",
      "requests-oauthlib                1.3.1\n",
      "requirements-parser              0.9.0\n",
      "rich                             13.7.1\n",
      "rpds-py                          0.18.0\n",
      "rpy2                             3.4.2\n",
      "rsa                              4.9\n",
      "safetensors                      0.4.3\n",
      "scikit-image                     0.19.3\n",
      "scikit-learn                     1.2.2\n",
      "scipy                            1.11.4\n",
      "scooby                           0.9.2\n",
      "scs                              3.2.4.post1\n",
      "seaborn                          0.13.1\n",
      "SecretStorage                    3.3.1\n",
      "Send2Trash                       1.8.3\n",
      "sentencepiece                    0.1.99\n",
      "setuptools                       67.7.2\n",
      "shapely                          2.0.4\n",
      "six                              1.16.0\n",
      "sklearn-pandas                   2.2.0\n",
      "smart-open                       6.4.0\n",
      "sniffio                          1.3.1\n",
      "snowballstemmer                  2.2.0\n",
      "sortedcontainers                 2.4.0\n",
      "soundfile                        0.12.1\n",
      "soupsieve                        2.5\n",
      "soxr                             0.3.7\n",
      "spacy                            3.7.4\n",
      "spacy-legacy                     3.0.12\n",
      "spacy-loggers                    1.0.5\n",
      "Sphinx                           5.0.2\n",
      "sphinxcontrib-applehelp          1.0.8\n",
      "sphinxcontrib-devhelp            1.0.6\n",
      "sphinxcontrib-htmlhelp           2.0.5\n",
      "sphinxcontrib-jsmath             1.0.1\n",
      "sphinxcontrib-qthelp             1.0.7\n",
      "sphinxcontrib-serializinghtml    1.1.10\n",
      "SQLAlchemy                       2.0.29\n",
      "sqlglot                          20.11.0\n",
      "sqlparse                         0.5.0\n",
      "srsly                            2.4.8\n",
      "stanio                           0.5.0\n",
      "statsmodels                      0.14.2\n",
      "StrEnum                          0.4.15\n",
      "sympy                            1.12\n",
      "tables                           3.8.0\n",
      "tabulate                         0.9.0\n",
      "tbb                              2021.12.0\n",
      "tblib                            3.0.0\n",
      "tenacity                         8.2.3\n",
      "tensorboard                      2.15.2\n",
      "tensorboard-data-server          0.7.2\n",
      "tensorflow                       2.15.0\n",
      "tensorflow-datasets              4.9.4\n",
      "tensorflow-estimator             2.15.0\n",
      "tensorflow-gcs-config            2.15.0\n",
      "tensorflow-hub                   0.16.1\n",
      "tensorflow-io-gcs-filesystem     0.37.0\n",
      "tensorflow-metadata              1.15.0\n",
      "tensorflow-probability           0.23.0\n",
      "tensorstore                      0.1.45\n",
      "termcolor                        2.4.0\n",
      "terminado                        0.18.1\n",
      "text-unidecode                   1.3\n",
      "textblob                         0.17.1\n",
      "tf_keras                         2.15.1\n",
      "tf-slim                          1.1.0\n",
      "thinc                            8.2.3\n",
      "threadpoolctl                    3.5.0\n",
      "tifffile                         2024.4.24\n",
      "tinycss2                         1.3.0\n",
      "tokenizers                       0.19.1\n",
      "toml                             0.10.2\n",
      "tomli                            2.0.1\n",
      "toolz                            0.12.1\n",
      "torch                            2.2.1+cu121\n",
      "torchaudio                       2.2.1+cu121\n",
      "torchdata                        0.7.1\n",
      "torchsummary                     1.5.1\n",
      "torchtext                        0.17.1\n",
      "torchvision                      0.17.1+cu121\n",
      "tornado                          6.3.3\n",
      "tqdm                             4.66.2\n",
      "traitlets                        5.7.1\n",
      "traittypes                       0.2.1\n",
      "transformers                     4.40.1\n",
      "triton                           2.2.0\n",
      "tweepy                           4.14.0\n",
      "typer                            0.9.4\n",
      "types-pytz                       2024.1.0.20240417\n",
      "types-setuptools                 69.5.0.20240423\n",
      "typing_extensions                4.11.0\n",
      "tzdata                           2024.1\n",
      "tzlocal                          5.2\n",
      "uc-micro-py                      1.0.3\n",
      "uritemplate                      4.1.1\n",
      "urllib3                          2.0.7\n",
      "vega-datasets                    0.9.0\n",
      "wadllib                          1.3.6\n",
      "wasabi                           1.1.2\n",
      "wcwidth                          0.2.13\n",
      "weasel                           0.3.4\n",
      "webcolors                        1.13\n",
      "webencodings                     0.5.1\n",
      "websocket-client                 1.8.0\n",
      "Werkzeug                         3.0.2\n",
      "wheel                            0.43.0\n",
      "widgetsnbextension               3.6.6\n",
      "wordcloud                        1.9.3\n",
      "wrapt                            1.14.1\n",
      "xarray                           2023.7.0\n",
      "xarray-einstats                  0.7.0\n",
      "xgboost                          2.0.3\n",
      "xlrd                             2.0.1\n",
      "xyzservices                      2024.4.0\n",
      "yarl                             1.9.4\n",
      "yellowbrick                      1.5\n",
      "yfinance                         0.2.38\n",
      "zict                             3.0.0\n",
      "zipp                             3.18.1\n"
     ]
    }
   ],
   "source": [
    "pip list"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "034f3ef1-960e-4cb3-a026-33bb5697ae11",
   "metadata": {
    "id": "034f3ef1-960e-4cb3-a026-33bb5697ae11"
   },
   "source": [
    "## Using Libraries in Python\n",
    "After installation, you can use the Library in your Python scripts as follows:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "914cc039-f470-46ad-86f2-cc53516c0d26",
   "metadata": {
    "id": "914cc039-f470-46ad-86f2-cc53516c0d26"
   },
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b894ace-b6c7-43b6-881d-128d415ba950",
   "metadata": {
    "id": "0b894ace-b6c7-43b6-881d-128d415ba950"
   },
   "source": [
    "This line imports the NumPy library and aliases it as np, allowing you to use its functions and modules with the np prefix.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "93a741c8-f9a9-4334-bd80-e365754d0754",
   "metadata": {},
   "outputs": [],
   "source": [
    "import osgeo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "8dd3bc99-65f4-49d4-abf0-adacc5895d39",
   "metadata": {
    "id": "8dd3bc99-65f4-49d4-abf0-adacc5895d39"
   },
   "outputs": [],
   "source": [
    "from osgeo import gdal"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67ecff42-8f68-4d11-9327-f06c6ce12f23",
   "metadata": {
    "id": "67ecff42-8f68-4d11-9327-f06c6ce12f23"
   },
   "source": [
    "## Upgrading a Library\n",
    "\n",
    "To upgrade an existing Library to the latest version, use:\n",
    "\n",
    "\n",
    "\n",
    "```ba\n",
    "pip install --upgrade package-namesh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "91f7f56b-7c8f-4a23-b39b-7dce4b4ac8fd",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "91f7f56b-7c8f-4a23-b39b-7dce4b4ac8fd",
    "outputId": "4c08b533-0e42-460d-f7ba-e22601f8a801"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: xarray in /usr/local/lib/python3.10/dist-packages (2023.7.0)\n",
      "Collecting xarray\n",
      "  Downloading xarray-2024.3.0-py3-none-any.whl (1.1 MB)\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.1/1.1 MB\u001b[0m \u001b[31m9.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[?25hRequirement already satisfied: numpy>=1.23 in /usr/local/lib/python3.10/dist-packages (from xarray) (1.25.2)\n",
      "Requirement already satisfied: packaging>=22 in /usr/local/lib/python3.10/dist-packages (from xarray) (24.0)\n",
      "Requirement already satisfied: pandas>=1.5 in /usr/local/lib/python3.10/dist-packages (from xarray) (2.0.3)\n",
      "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from pandas>=1.5->xarray) (2.8.2)\n",
      "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=1.5->xarray) (2023.4)\n",
      "Requirement already satisfied: tzdata>=2022.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=1.5->xarray) (2024.1)\n",
      "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.2->pandas>=1.5->xarray) (1.16.0)\n",
      "Installing collected packages: xarray\n",
      "  Attempting uninstall: xarray\n",
      "    Found existing installation: xarray 2023.7.0\n",
      "    Uninstalling xarray-2023.7.0:\n",
      "      Successfully uninstalled xarray-2023.7.0\n",
      "Successfully installed xarray-2024.3.0\n"
     ]
    }
   ],
   "source": [
    "pip install --upgrade xarray"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c720fda7-de15-4ab5-8a73-0c7b783476f2",
   "metadata": {
    "id": "c720fda7-de15-4ab5-8a73-0c7b783476f2"
   },
   "source": [
    "## Uninstalling a Library\n",
    "\n",
    "If you need to remove a Library, use:\n",
    "\n",
    "```bash\n",
    "pip uninstall package-name\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "5dc4f472-8d76-4601-946e-c524f96acc55",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "5dc4f472-8d76-4601-946e-c524f96acc55",
    "outputId": "250c99fc-4f42-4469-c69a-404b8ebe926c"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found existing installation: xarray 2024.3.0\n",
      "Uninstalling xarray-2024.3.0:\n",
      "  Would remove:\n",
      "    /usr/local/lib/python3.10/dist-packages/xarray-2024.3.0.dist-info/*\n",
      "    /usr/local/lib/python3.10/dist-packages/xarray/*\n",
      "Proceed (Y/n)? Y\n",
      "  Successfully uninstalled xarray-2024.3.0\n"
     ]
    }
   ],
   "source": [
    "pip uninstall xarray"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e2ac747f-058c-4f79-a89c-c9e254402f1b",
   "metadata": {
    "id": "e2ac747f-058c-4f79-a89c-c9e254402f1b"
   },
   "source": [
    "# DataFrame\n",
    "A DataFrame is a data structure that organizes data into a 2-dimensional table of rows and columns, much like a spreadsheet. DataFrames are one of the most common data structures used in modern data analytics because they are a flexible and intuitive way of storing and working with data."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "520e1ac2",
   "metadata": {
    "id": "520e1ac2"
   },
   "source": [
    "## Importing DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "45cbfd67",
   "metadata": {
    "id": "45cbfd67"
   },
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "05b74a8f",
   "metadata": {
    "id": "05b74a8f"
   },
   "outputs": [],
   "source": [
    "df= pd.read_csv('Weather_Data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "98ddbd3a-7fc3-4ae9-8203-db2e8d9dd87e",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 444
    },
    "id": "98ddbd3a-7fc3-4ae9-8203-db2e8d9dd87e",
    "outputId": "dc335c61-f1e2-4734-a204-47d7b000e4bf"
   },
   "outputs": [
    {
     "data": {
      "application/vnd.google.colaboratory.intrinsic+json": {
       "type": "dataframe",
       "variable_name": "df"
      },
      "text/html": [
       "\n",
       "  <div id=\"df-ff9eeac3-6a33-445c-a189-31d2ba7e7a2d\" class=\"colab-df-container\">\n",
       "    <div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>MinTemp</th>\n",
       "      <th>MaxTemp</th>\n",
       "      <th>Rainfall</th>\n",
       "      <th>Evaporation</th>\n",
       "      <th>Sunshine</th>\n",
       "      <th>WindGustDir</th>\n",
       "      <th>WindGustSpeed</th>\n",
       "      <th>WindDir9am</th>\n",
       "      <th>WindDir3pm</th>\n",
       "      <th>...</th>\n",
       "      <th>Humidity9am</th>\n",
       "      <th>Humidity3pm</th>\n",
       "      <th>Pressure9am</th>\n",
       "      <th>Pressure3pm</th>\n",
       "      <th>Cloud9am</th>\n",
       "      <th>Cloud3pm</th>\n",
       "      <th>Temp9am</th>\n",
       "      <th>Temp3pm</th>\n",
       "      <th>RainToday</th>\n",
       "      <th>RainTomorrow</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2/1/2008</td>\n",
       "      <td>19.5</td>\n",
       "      <td>22.4</td>\n",
       "      <td>15.6</td>\n",
       "      <td>6.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>W</td>\n",
       "      <td>41</td>\n",
       "      <td>S</td>\n",
       "      <td>SSW</td>\n",
       "      <td>...</td>\n",
       "      <td>92</td>\n",
       "      <td>84</td>\n",
       "      <td>1017.6</td>\n",
       "      <td>1017.4</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>20.7</td>\n",
       "      <td>20.9</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2/2/2008</td>\n",
       "      <td>19.5</td>\n",
       "      <td>25.6</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.4</td>\n",
       "      <td>2.7</td>\n",
       "      <td>W</td>\n",
       "      <td>41</td>\n",
       "      <td>W</td>\n",
       "      <td>E</td>\n",
       "      <td>...</td>\n",
       "      <td>83</td>\n",
       "      <td>73</td>\n",
       "      <td>1017.9</td>\n",
       "      <td>1016.4</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>22.4</td>\n",
       "      <td>24.8</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2/3/2008</td>\n",
       "      <td>21.6</td>\n",
       "      <td>24.5</td>\n",
       "      <td>6.6</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.1</td>\n",
       "      <td>W</td>\n",
       "      <td>41</td>\n",
       "      <td>ESE</td>\n",
       "      <td>ESE</td>\n",
       "      <td>...</td>\n",
       "      <td>88</td>\n",
       "      <td>86</td>\n",
       "      <td>1016.7</td>\n",
       "      <td>1015.6</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2/4/2008</td>\n",
       "      <td>20.2</td>\n",
       "      <td>22.8</td>\n",
       "      <td>18.8</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>W</td>\n",
       "      <td>41</td>\n",
       "      <td>NNE</td>\n",
       "      <td>E</td>\n",
       "      <td>...</td>\n",
       "      <td>83</td>\n",
       "      <td>90</td>\n",
       "      <td>1014.2</td>\n",
       "      <td>1011.8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>21.4</td>\n",
       "      <td>20.9</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2/5/2008</td>\n",
       "      <td>19.7</td>\n",
       "      <td>25.7</td>\n",
       "      <td>77.4</td>\n",
       "      <td>4.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>W</td>\n",
       "      <td>41</td>\n",
       "      <td>NNE</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>88</td>\n",
       "      <td>74</td>\n",
       "      <td>1008.3</td>\n",
       "      <td>1004.8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>22.5</td>\n",
       "      <td>25.5</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3266</th>\n",
       "      <td>6/21/2017</td>\n",
       "      <td>8.6</td>\n",
       "      <td>19.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.8</td>\n",
       "      <td>SSE</td>\n",
       "      <td>37</td>\n",
       "      <td>W</td>\n",
       "      <td>SSE</td>\n",
       "      <td>...</td>\n",
       "      <td>73</td>\n",
       "      <td>52</td>\n",
       "      <td>1025.9</td>\n",
       "      <td>1025.3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>10.5</td>\n",
       "      <td>17.9</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3267</th>\n",
       "      <td>6/22/2017</td>\n",
       "      <td>9.3</td>\n",
       "      <td>19.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>9.2</td>\n",
       "      <td>W</td>\n",
       "      <td>30</td>\n",
       "      <td>W</td>\n",
       "      <td>ESE</td>\n",
       "      <td>...</td>\n",
       "      <td>78</td>\n",
       "      <td>53</td>\n",
       "      <td>1028.5</td>\n",
       "      <td>1024.6</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>11.0</td>\n",
       "      <td>18.7</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3268</th>\n",
       "      <td>6/23/2017</td>\n",
       "      <td>9.4</td>\n",
       "      <td>17.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.4</td>\n",
       "      <td>2.7</td>\n",
       "      <td>W</td>\n",
       "      <td>24</td>\n",
       "      <td>WNW</td>\n",
       "      <td>N</td>\n",
       "      <td>...</td>\n",
       "      <td>85</td>\n",
       "      <td>56</td>\n",
       "      <td>1020.8</td>\n",
       "      <td>1015.0</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>10.2</td>\n",
       "      <td>17.3</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3269</th>\n",
       "      <td>6/24/2017</td>\n",
       "      <td>10.1</td>\n",
       "      <td>19.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>9.3</td>\n",
       "      <td>W</td>\n",
       "      <td>43</td>\n",
       "      <td>W</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>56</td>\n",
       "      <td>35</td>\n",
       "      <td>1017.3</td>\n",
       "      <td>1015.1</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>12.4</td>\n",
       "      <td>19.0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3270</th>\n",
       "      <td>6/25/2017</td>\n",
       "      <td>7.6</td>\n",
       "      <td>19.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.4</td>\n",
       "      <td>9.4</td>\n",
       "      <td>W</td>\n",
       "      <td>35</td>\n",
       "      <td>W</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>73</td>\n",
       "      <td>32</td>\n",
       "      <td>1018.6</td>\n",
       "      <td>1015.4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>9.4</td>\n",
       "      <td>18.8</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3271 rows × 22 columns</p>\n",
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       "\n",
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       "    async function quickchart(key) {\n",
       "      const quickchartButtonEl =\n",
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       "        const charts = await google.colab.kernel.invokeFunction(\n",
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       "  </script>\n",
       "</div>\n",
       "    </div>\n",
       "  </div>\n"
      ],
      "text/plain": [
       "           Date  MinTemp  MaxTemp  Rainfall  Evaporation  Sunshine  \\\n",
       "0      2/1/2008     19.5     22.4      15.6          6.2       0.0   \n",
       "1      2/2/2008     19.5     25.6       6.0          3.4       2.7   \n",
       "2      2/3/2008     21.6     24.5       6.6          2.4       0.1   \n",
       "3      2/4/2008     20.2     22.8      18.8          2.2       0.0   \n",
       "4      2/5/2008     19.7     25.7      77.4          4.8       0.0   \n",
       "...         ...      ...      ...       ...          ...       ...   \n",
       "3266  6/21/2017      8.6     19.6       0.0          2.0       7.8   \n",
       "3267  6/22/2017      9.3     19.2       0.0          2.0       9.2   \n",
       "3268  6/23/2017      9.4     17.7       0.0          2.4       2.7   \n",
       "3269  6/24/2017     10.1     19.3       0.0          1.4       9.3   \n",
       "3270  6/25/2017      7.6     19.3       0.0          3.4       9.4   \n",
       "\n",
       "     WindGustDir  WindGustSpeed WindDir9am WindDir3pm  ...  Humidity9am  \\\n",
       "0              W             41          S        SSW  ...           92   \n",
       "1              W             41          W          E  ...           83   \n",
       "2              W             41        ESE        ESE  ...           88   \n",
       "3              W             41        NNE          E  ...           83   \n",
       "4              W             41        NNE          W  ...           88   \n",
       "...          ...            ...        ...        ...  ...          ...   \n",
       "3266         SSE             37          W        SSE  ...           73   \n",
       "3267           W             30          W        ESE  ...           78   \n",
       "3268           W             24        WNW          N  ...           85   \n",
       "3269           W             43          W          W  ...           56   \n",
       "3270           W             35          W          W  ...           73   \n",
       "\n",
       "      Humidity3pm  Pressure9am  Pressure3pm  Cloud9am  Cloud3pm  Temp9am  \\\n",
       "0              84       1017.6       1017.4         8         8     20.7   \n",
       "1              73       1017.9       1016.4         7         7     22.4   \n",
       "2              86       1016.7       1015.6         7         8     23.5   \n",
       "3              90       1014.2       1011.8         8         8     21.4   \n",
       "4              74       1008.3       1004.8         8         8     22.5   \n",
       "...           ...          ...          ...       ...       ...      ...   \n",
       "3266           52       1025.9       1025.3         2         2     10.5   \n",
       "3267           53       1028.5       1024.6         2         2     11.0   \n",
       "3268           56       1020.8       1015.0         6         6     10.2   \n",
       "3269           35       1017.3       1015.1         5         2     12.4   \n",
       "3270           32       1018.6       1015.4         1         1      9.4   \n",
       "\n",
       "      Temp3pm  RainToday  RainTomorrow  \n",
       "0        20.9        Yes           Yes  \n",
       "1        24.8        Yes           Yes  \n",
       "2        23.0        Yes           Yes  \n",
       "3        20.9        Yes           Yes  \n",
       "4        25.5        Yes           Yes  \n",
       "...       ...        ...           ...  \n",
       "3266     17.9         No            No  \n",
       "3267     18.7         No            No  \n",
       "3268     17.3         No            No  \n",
       "3269     19.0         No            No  \n",
       "3270     18.8         No            No  \n",
       "\n",
       "[3271 rows x 22 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36f7e8db-a23e-4a1d-affc-67234ba1d47e",
   "metadata": {
    "id": "36f7e8db-a23e-4a1d-affc-67234ba1d47e"
   },
   "source": [
    "## `df.head()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "dace1ba6",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 256
    },
    "id": "dace1ba6",
    "outputId": "3ab6d6cb-163b-451d-f386-f3623d255d5c"
   },
   "outputs": [
    {
     "data": {
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       "\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>MinTemp</th>\n",
       "      <th>MaxTemp</th>\n",
       "      <th>Rainfall</th>\n",
       "      <th>Evaporation</th>\n",
       "      <th>Sunshine</th>\n",
       "      <th>WindGustDir</th>\n",
       "      <th>WindGustSpeed</th>\n",
       "      <th>WindDir9am</th>\n",
       "      <th>WindDir3pm</th>\n",
       "      <th>...</th>\n",
       "      <th>Humidity9am</th>\n",
       "      <th>Humidity3pm</th>\n",
       "      <th>Pressure9am</th>\n",
       "      <th>Pressure3pm</th>\n",
       "      <th>Cloud9am</th>\n",
       "      <th>Cloud3pm</th>\n",
       "      <th>Temp9am</th>\n",
       "      <th>Temp3pm</th>\n",
       "      <th>RainToday</th>\n",
       "      <th>RainTomorrow</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2/1/2008</td>\n",
       "      <td>19.5</td>\n",
       "      <td>22.4</td>\n",
       "      <td>15.6</td>\n",
       "      <td>6.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>W</td>\n",
       "      <td>41</td>\n",
       "      <td>S</td>\n",
       "      <td>SSW</td>\n",
       "      <td>...</td>\n",
       "      <td>92</td>\n",
       "      <td>84</td>\n",
       "      <td>1017.6</td>\n",
       "      <td>1017.4</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>20.7</td>\n",
       "      <td>20.9</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2/2/2008</td>\n",
       "      <td>19.5</td>\n",
       "      <td>25.6</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.4</td>\n",
       "      <td>2.7</td>\n",
       "      <td>W</td>\n",
       "      <td>41</td>\n",
       "      <td>W</td>\n",
       "      <td>E</td>\n",
       "      <td>...</td>\n",
       "      <td>83</td>\n",
       "      <td>73</td>\n",
       "      <td>1017.9</td>\n",
       "      <td>1016.4</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>22.4</td>\n",
       "      <td>24.8</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2/3/2008</td>\n",
       "      <td>21.6</td>\n",
       "      <td>24.5</td>\n",
       "      <td>6.6</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.1</td>\n",
       "      <td>W</td>\n",
       "      <td>41</td>\n",
       "      <td>ESE</td>\n",
       "      <td>ESE</td>\n",
       "      <td>...</td>\n",
       "      <td>88</td>\n",
       "      <td>86</td>\n",
       "      <td>1016.7</td>\n",
       "      <td>1015.6</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2/4/2008</td>\n",
       "      <td>20.2</td>\n",
       "      <td>22.8</td>\n",
       "      <td>18.8</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>W</td>\n",
       "      <td>41</td>\n",
       "      <td>NNE</td>\n",
       "      <td>E</td>\n",
       "      <td>...</td>\n",
       "      <td>83</td>\n",
       "      <td>90</td>\n",
       "      <td>1014.2</td>\n",
       "      <td>1011.8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>21.4</td>\n",
       "      <td>20.9</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2/5/2008</td>\n",
       "      <td>19.7</td>\n",
       "      <td>25.7</td>\n",
       "      <td>77.4</td>\n",
       "      <td>4.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>W</td>\n",
       "      <td>41</td>\n",
       "      <td>NNE</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>88</td>\n",
       "      <td>74</td>\n",
       "      <td>1008.3</td>\n",
       "      <td>1004.8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>22.5</td>\n",
       "      <td>25.5</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "<p>5 rows × 22 columns</p>\n",
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       "  [theme=dark] .colab-df-quickchart {\n",
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       "\n",
       "  .colab-df-quickchart {\n",
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       "    width: 32px;\n",
       "  }\n",
       "\n",
       "  .colab-df-quickchart:hover {\n",
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       "  .colab-df-quickchart-complete:disabled,\n",
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       "    background-color: var(--disabled-bg-color);\n",
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       "\n",
       "  .colab-df-spinner {\n",
       "    border: 2px solid var(--fill-color);\n",
       "    border-color: transparent;\n",
       "    border-bottom-color: var(--fill-color);\n",
       "    animation:\n",
       "      spin 1s steps(1) infinite;\n",
       "  }\n",
       "\n",
       "  @keyframes spin {\n",
       "    0% {\n",
       "      border-color: transparent;\n",
       "      border-bottom-color: var(--fill-color);\n",
       "      border-left-color: var(--fill-color);\n",
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       "      border-bottom-color: var(--fill-color);\n",
       "    }\n",
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       "</style>\n",
       "\n",
       "  <script>\n",
       "    async function quickchart(key) {\n",
       "      const quickchartButtonEl =\n",
       "        document.querySelector('#' + key + ' button');\n",
       "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
       "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
       "      try {\n",
       "        const charts = await google.colab.kernel.invokeFunction(\n",
       "            'suggestCharts', [key], {});\n",
       "      } catch (error) {\n",
       "        console.error('Error during call to suggestCharts:', error);\n",
       "      }\n",
       "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
       "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
       "    }\n",
       "    (() => {\n",
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       "      quickchartButtonEl.style.display =\n",
       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
       "    })();\n",
       "  </script>\n",
       "</div>\n",
       "    </div>\n",
       "  </div>\n"
      ],
      "text/plain": [
       "       Date  MinTemp  MaxTemp  Rainfall  Evaporation  Sunshine WindGustDir  \\\n",
       "0  2/1/2008     19.5     22.4      15.6          6.2       0.0           W   \n",
       "1  2/2/2008     19.5     25.6       6.0          3.4       2.7           W   \n",
       "2  2/3/2008     21.6     24.5       6.6          2.4       0.1           W   \n",
       "3  2/4/2008     20.2     22.8      18.8          2.2       0.0           W   \n",
       "4  2/5/2008     19.7     25.7      77.4          4.8       0.0           W   \n",
       "\n",
       "   WindGustSpeed WindDir9am WindDir3pm  ...  Humidity9am  Humidity3pm  \\\n",
       "0             41          S        SSW  ...           92           84   \n",
       "1             41          W          E  ...           83           73   \n",
       "2             41        ESE        ESE  ...           88           86   \n",
       "3             41        NNE          E  ...           83           90   \n",
       "4             41        NNE          W  ...           88           74   \n",
       "\n",
       "   Pressure9am  Pressure3pm  Cloud9am  Cloud3pm  Temp9am  Temp3pm  RainToday  \\\n",
       "0       1017.6       1017.4         8         8     20.7     20.9        Yes   \n",
       "1       1017.9       1016.4         7         7     22.4     24.8        Yes   \n",
       "2       1016.7       1015.6         7         8     23.5     23.0        Yes   \n",
       "3       1014.2       1011.8         8         8     21.4     20.9        Yes   \n",
       "4       1008.3       1004.8         8         8     22.5     25.5        Yes   \n",
       "\n",
       "   RainTomorrow  \n",
       "0           Yes  \n",
       "1           Yes  \n",
       "2           Yes  \n",
       "3           Yes  \n",
       "4           Yes  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "59ce937c-4eb6-4477-a3e8-e13172865af9",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 412
    },
    "id": "59ce937c-4eb6-4477-a3e8-e13172865af9",
    "outputId": "eb9fe875-9fbc-4968-e832-7cd0bfe9f00c"
   },
   "outputs": [
    {
     "data": {
      "application/vnd.google.colaboratory.intrinsic+json": {
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       "variable_name": "df"
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      "text/html": [
       "\n",
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       "    <div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>MinTemp</th>\n",
       "      <th>MaxTemp</th>\n",
       "      <th>Rainfall</th>\n",
       "      <th>Evaporation</th>\n",
       "      <th>Sunshine</th>\n",
       "      <th>WindGustDir</th>\n",
       "      <th>WindGustSpeed</th>\n",
       "      <th>WindDir9am</th>\n",
       "      <th>WindDir3pm</th>\n",
       "      <th>...</th>\n",
       "      <th>Humidity9am</th>\n",
       "      <th>Humidity3pm</th>\n",
       "      <th>Pressure9am</th>\n",
       "      <th>Pressure3pm</th>\n",
       "      <th>Cloud9am</th>\n",
       "      <th>Cloud3pm</th>\n",
       "      <th>Temp9am</th>\n",
       "      <th>Temp3pm</th>\n",
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       "      <th>RainTomorrow</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2/1/2008</td>\n",
       "      <td>19.5</td>\n",
       "      <td>22.4</td>\n",
       "      <td>15.6</td>\n",
       "      <td>6.2</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>41</td>\n",
       "      <td>S</td>\n",
       "      <td>SSW</td>\n",
       "      <td>...</td>\n",
       "      <td>92</td>\n",
       "      <td>84</td>\n",
       "      <td>1017.6</td>\n",
       "      <td>1017.4</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>20.7</td>\n",
       "      <td>20.9</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2/2/2008</td>\n",
       "      <td>19.5</td>\n",
       "      <td>25.6</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.4</td>\n",
       "      <td>2.7</td>\n",
       "      <td>W</td>\n",
       "      <td>41</td>\n",
       "      <td>W</td>\n",
       "      <td>E</td>\n",
       "      <td>...</td>\n",
       "      <td>83</td>\n",
       "      <td>73</td>\n",
       "      <td>1017.9</td>\n",
       "      <td>1016.4</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>22.4</td>\n",
       "      <td>24.8</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2/3/2008</td>\n",
       "      <td>21.6</td>\n",
       "      <td>24.5</td>\n",
       "      <td>6.6</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.1</td>\n",
       "      <td>W</td>\n",
       "      <td>41</td>\n",
       "      <td>ESE</td>\n",
       "      <td>ESE</td>\n",
       "      <td>...</td>\n",
       "      <td>88</td>\n",
       "      <td>86</td>\n",
       "      <td>1016.7</td>\n",
       "      <td>1015.6</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2/4/2008</td>\n",
       "      <td>20.2</td>\n",
       "      <td>22.8</td>\n",
       "      <td>18.8</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>W</td>\n",
       "      <td>41</td>\n",
       "      <td>NNE</td>\n",
       "      <td>E</td>\n",
       "      <td>...</td>\n",
       "      <td>83</td>\n",
       "      <td>90</td>\n",
       "      <td>1014.2</td>\n",
       "      <td>1011.8</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>21.4</td>\n",
       "      <td>20.9</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2/5/2008</td>\n",
       "      <td>19.7</td>\n",
       "      <td>25.7</td>\n",
       "      <td>77.4</td>\n",
       "      <td>4.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>W</td>\n",
       "      <td>41</td>\n",
       "      <td>NNE</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>88</td>\n",
       "      <td>74</td>\n",
       "      <td>1008.3</td>\n",
       "      <td>1004.8</td>\n",
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       "      <td>8</td>\n",
       "      <td>22.5</td>\n",
       "      <td>25.5</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2/6/2008</td>\n",
       "      <td>20.2</td>\n",
       "      <td>27.2</td>\n",
       "      <td>1.6</td>\n",
       "      <td>2.6</td>\n",
       "      <td>8.6</td>\n",
       "      <td>W</td>\n",
       "      <td>41</td>\n",
       "      <td>W</td>\n",
       "      <td>ENE</td>\n",
       "      <td>...</td>\n",
       "      <td>69</td>\n",
       "      <td>62</td>\n",
       "      <td>1002.7</td>\n",
       "      <td>998.6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>23.8</td>\n",
       "      <td>26.0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2/7/2008</td>\n",
       "      <td>18.6</td>\n",
       "      <td>26.3</td>\n",
       "      <td>6.2</td>\n",
       "      <td>5.2</td>\n",
       "      <td>5.2</td>\n",
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       "      <td>41</td>\n",
       "      <td>W</td>\n",
       "      <td>S</td>\n",
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       "      <td>75</td>\n",
       "      <td>80</td>\n",
       "      <td>999.0</td>\n",
       "      <td>1000.3</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>21.7</td>\n",
       "      <td>22.3</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2/8/2008</td>\n",
       "      <td>17.2</td>\n",
       "      <td>22.3</td>\n",
       "      <td>27.6</td>\n",
       "      <td>5.8</td>\n",
       "      <td>2.1</td>\n",
       "      <td>W</td>\n",
       "      <td>41</td>\n",
       "      <td>S</td>\n",
       "      <td>SE</td>\n",
       "      <td>...</td>\n",
       "      <td>77</td>\n",
       "      <td>61</td>\n",
       "      <td>1008.3</td>\n",
       "      <td>1007.4</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>18.9</td>\n",
       "      <td>21.1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2/9/2008</td>\n",
       "      <td>16.4</td>\n",
       "      <td>20.8</td>\n",
       "      <td>12.6</td>\n",
       "      <td>4.8</td>\n",
       "      <td>3.0</td>\n",
       "      <td>W</td>\n",
       "      <td>41</td>\n",
       "      <td>SSW</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>92</td>\n",
       "      <td>91</td>\n",
       "      <td>1006.4</td>\n",
       "      <td>1007.6</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>17.1</td>\n",
       "      <td>16.5</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2/10/2008</td>\n",
       "      <td>14.6</td>\n",
       "      <td>24.2</td>\n",
       "      <td>8.8</td>\n",
       "      <td>4.4</td>\n",
       "      <td>10.1</td>\n",
       "      <td>W</td>\n",
       "      <td>41</td>\n",
       "      <td>W</td>\n",
       "      <td>SSE</td>\n",
       "      <td>...</td>\n",
       "      <td>80</td>\n",
       "      <td>53</td>\n",
       "      <td>1014.0</td>\n",
       "      <td>1013.4</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>17.2</td>\n",
       "      <td>23.3</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 22 columns</p>\n",
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       "  .colab-df-quickchart:hover {\n",
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       "\n",
       "  @keyframes spin {\n",
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       "\n",
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       "    async function quickchart(key) {\n",
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       "        const charts = await google.colab.kernel.invokeFunction(\n",
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       "  </script>\n",
       "</div>\n",
       "    </div>\n",
       "  </div>\n"
      ],
      "text/plain": [
       "        Date  MinTemp  MaxTemp  Rainfall  Evaporation  Sunshine WindGustDir  \\\n",
       "0   2/1/2008     19.5     22.4      15.6          6.2       0.0           W   \n",
       "1   2/2/2008     19.5     25.6       6.0          3.4       2.7           W   \n",
       "2   2/3/2008     21.6     24.5       6.6          2.4       0.1           W   \n",
       "3   2/4/2008     20.2     22.8      18.8          2.2       0.0           W   \n",
       "4   2/5/2008     19.7     25.7      77.4          4.8       0.0           W   \n",
       "5   2/6/2008     20.2     27.2       1.6          2.6       8.6           W   \n",
       "6   2/7/2008     18.6     26.3       6.2          5.2       5.2           W   \n",
       "7   2/8/2008     17.2     22.3      27.6          5.8       2.1           W   \n",
       "8   2/9/2008     16.4     20.8      12.6          4.8       3.0           W   \n",
       "9  2/10/2008     14.6     24.2       8.8          4.4      10.1           W   \n",
       "\n",
       "   WindGustSpeed WindDir9am WindDir3pm  ...  Humidity9am  Humidity3pm  \\\n",
       "0             41          S        SSW  ...           92           84   \n",
       "1             41          W          E  ...           83           73   \n",
       "2             41        ESE        ESE  ...           88           86   \n",
       "3             41        NNE          E  ...           83           90   \n",
       "4             41        NNE          W  ...           88           74   \n",
       "5             41          W        ENE  ...           69           62   \n",
       "6             41          W          S  ...           75           80   \n",
       "7             41          S         SE  ...           77           61   \n",
       "8             41        SSW          W  ...           92           91   \n",
       "9             41          W        SSE  ...           80           53   \n",
       "\n",
       "   Pressure9am  Pressure3pm  Cloud9am  Cloud3pm  Temp9am  Temp3pm  RainToday  \\\n",
       "0       1017.6       1017.4         8         8     20.7     20.9        Yes   \n",
       "1       1017.9       1016.4         7         7     22.4     24.8        Yes   \n",
       "2       1016.7       1015.6         7         8     23.5     23.0        Yes   \n",
       "3       1014.2       1011.8         8         8     21.4     20.9        Yes   \n",
       "4       1008.3       1004.8         8         8     22.5     25.5        Yes   \n",
       "5       1002.7        998.6         6         6     23.8     26.0        Yes   \n",
       "6        999.0       1000.3         4         7     21.7     22.3        Yes   \n",
       "7       1008.3       1007.4         7         8     18.9     21.1        Yes   \n",
       "8       1006.4       1007.6         7         7     17.1     16.5        Yes   \n",
       "9       1014.0       1013.4         4         2     17.2     23.3        Yes   \n",
       "\n",
       "   RainTomorrow  \n",
       "0           Yes  \n",
       "1           Yes  \n",
       "2           Yes  \n",
       "3           Yes  \n",
       "4           Yes  \n",
       "5           Yes  \n",
       "6           Yes  \n",
       "7           Yes  \n",
       "8           Yes  \n",
       "9            No  \n",
       "\n",
       "[10 rows x 22 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "869d7d9e-1310-4dba-bc15-77b182ee936a",
   "metadata": {
    "id": "869d7d9e-1310-4dba-bc15-77b182ee936a"
   },
   "source": [
    "The `df.head()` function in Python is used with a DataFrame object, typically from the `pandas` library. It returns the first **n** rows of the DataFrame for quick inspection. By default, if no parameter is specified, `df.head()` will return the first **5** rows. You can also specify the number of rows you want to display by passing an integer as an argument, like `df.head(10)` to display the first 10 rows."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4993e903-ade6-4e00-be23-85bcfe791e2b",
   "metadata": {
    "id": "4993e903-ade6-4e00-be23-85bcfe791e2b"
   },
   "source": [
    "## `df.tail()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "130558de",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 256
    },
    "id": "130558de",
    "outputId": "ebbc41b3-3729-410b-ca69-3af27123d109"
   },
   "outputs": [
    {
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       "\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>MinTemp</th>\n",
       "      <th>MaxTemp</th>\n",
       "      <th>Rainfall</th>\n",
       "      <th>Evaporation</th>\n",
       "      <th>Sunshine</th>\n",
       "      <th>WindGustDir</th>\n",
       "      <th>WindGustSpeed</th>\n",
       "      <th>WindDir9am</th>\n",
       "      <th>WindDir3pm</th>\n",
       "      <th>...</th>\n",
       "      <th>Humidity9am</th>\n",
       "      <th>Humidity3pm</th>\n",
       "      <th>Pressure9am</th>\n",
       "      <th>Pressure3pm</th>\n",
       "      <th>Cloud9am</th>\n",
       "      <th>Cloud3pm</th>\n",
       "      <th>Temp9am</th>\n",
       "      <th>Temp3pm</th>\n",
       "      <th>RainToday</th>\n",
       "      <th>RainTomorrow</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3266</th>\n",
       "      <td>6/21/2017</td>\n",
       "      <td>8.6</td>\n",
       "      <td>19.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.8</td>\n",
       "      <td>SSE</td>\n",
       "      <td>37</td>\n",
       "      <td>W</td>\n",
       "      <td>SSE</td>\n",
       "      <td>...</td>\n",
       "      <td>73</td>\n",
       "      <td>52</td>\n",
       "      <td>1025.9</td>\n",
       "      <td>1025.3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>10.5</td>\n",
       "      <td>17.9</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3267</th>\n",
       "      <td>6/22/2017</td>\n",
       "      <td>9.3</td>\n",
       "      <td>19.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>9.2</td>\n",
       "      <td>W</td>\n",
       "      <td>30</td>\n",
       "      <td>W</td>\n",
       "      <td>ESE</td>\n",
       "      <td>...</td>\n",
       "      <td>78</td>\n",
       "      <td>53</td>\n",
       "      <td>1028.5</td>\n",
       "      <td>1024.6</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>11.0</td>\n",
       "      <td>18.7</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3268</th>\n",
       "      <td>6/23/2017</td>\n",
       "      <td>9.4</td>\n",
       "      <td>17.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.4</td>\n",
       "      <td>2.7</td>\n",
       "      <td>W</td>\n",
       "      <td>24</td>\n",
       "      <td>WNW</td>\n",
       "      <td>N</td>\n",
       "      <td>...</td>\n",
       "      <td>85</td>\n",
       "      <td>56</td>\n",
       "      <td>1020.8</td>\n",
       "      <td>1015.0</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>10.2</td>\n",
       "      <td>17.3</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3269</th>\n",
       "      <td>6/24/2017</td>\n",
       "      <td>10.1</td>\n",
       "      <td>19.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>9.3</td>\n",
       "      <td>W</td>\n",
       "      <td>43</td>\n",
       "      <td>W</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>56</td>\n",
       "      <td>35</td>\n",
       "      <td>1017.3</td>\n",
       "      <td>1015.1</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>12.4</td>\n",
       "      <td>19.0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3270</th>\n",
       "      <td>6/25/2017</td>\n",
       "      <td>7.6</td>\n",
       "      <td>19.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.4</td>\n",
       "      <td>9.4</td>\n",
       "      <td>W</td>\n",
       "      <td>35</td>\n",
       "      <td>W</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>73</td>\n",
       "      <td>32</td>\n",
       "      <td>1018.6</td>\n",
       "      <td>1015.4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>9.4</td>\n",
       "      <td>18.8</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
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       "\n",
       "  .colab-df-quickchart {\n",
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       "    width: 32px;\n",
       "  }\n",
       "\n",
       "  .colab-df-quickchart:hover {\n",
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       "  .colab-df-quickchart-complete:disabled,\n",
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       "\n",
       "  @keyframes spin {\n",
       "    0% {\n",
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       "      border-left-color: var(--fill-color);\n",
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       "\n",
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       "    async function quickchart(key) {\n",
       "      const quickchartButtonEl =\n",
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       "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
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       "        const charts = await google.colab.kernel.invokeFunction(\n",
       "            'suggestCharts', [key], {});\n",
       "      } catch (error) {\n",
       "        console.error('Error during call to suggestCharts:', error);\n",
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       "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
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       "    (() => {\n",
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       "      quickchartButtonEl.style.display =\n",
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       "  </script>\n",
       "</div>\n",
       "    </div>\n",
       "  </div>\n"
      ],
      "text/plain": [
       "           Date  MinTemp  MaxTemp  Rainfall  Evaporation  Sunshine  \\\n",
       "3266  6/21/2017      8.6     19.6       0.0          2.0       7.8   \n",
       "3267  6/22/2017      9.3     19.2       0.0          2.0       9.2   \n",
       "3268  6/23/2017      9.4     17.7       0.0          2.4       2.7   \n",
       "3269  6/24/2017     10.1     19.3       0.0          1.4       9.3   \n",
       "3270  6/25/2017      7.6     19.3       0.0          3.4       9.4   \n",
       "\n",
       "     WindGustDir  WindGustSpeed WindDir9am WindDir3pm  ...  Humidity9am  \\\n",
       "3266         SSE             37          W        SSE  ...           73   \n",
       "3267           W             30          W        ESE  ...           78   \n",
       "3268           W             24        WNW          N  ...           85   \n",
       "3269           W             43          W          W  ...           56   \n",
       "3270           W             35          W          W  ...           73   \n",
       "\n",
       "      Humidity3pm  Pressure9am  Pressure3pm  Cloud9am  Cloud3pm  Temp9am  \\\n",
       "3266           52       1025.9       1025.3         2         2     10.5   \n",
       "3267           53       1028.5       1024.6         2         2     11.0   \n",
       "3268           56       1020.8       1015.0         6         6     10.2   \n",
       "3269           35       1017.3       1015.1         5         2     12.4   \n",
       "3270           32       1018.6       1015.4         1         1      9.4   \n",
       "\n",
       "      Temp3pm  RainToday  RainTomorrow  \n",
       "3266     17.9         No            No  \n",
       "3267     18.7         No            No  \n",
       "3268     17.3         No            No  \n",
       "3269     19.0         No            No  \n",
       "3270     18.8         No            No  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "7e6cd3b7-cbaa-429a-bb30-8eeac6afad00",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 412
    },
    "id": "7e6cd3b7-cbaa-429a-bb30-8eeac6afad00",
    "outputId": "9db4a6d8-5a15-42ef-af1f-b078fe39a5fb"
   },
   "outputs": [
    {
     "data": {
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       "\n",
       "  <div id=\"df-4ae53c9b-3934-42b1-8362-19c51af377e3\" class=\"colab-df-container\">\n",
       "    <div>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>MinTemp</th>\n",
       "      <th>MaxTemp</th>\n",
       "      <th>Rainfall</th>\n",
       "      <th>Evaporation</th>\n",
       "      <th>Sunshine</th>\n",
       "      <th>WindGustDir</th>\n",
       "      <th>WindGustSpeed</th>\n",
       "      <th>WindDir9am</th>\n",
       "      <th>WindDir3pm</th>\n",
       "      <th>...</th>\n",
       "      <th>Humidity9am</th>\n",
       "      <th>Humidity3pm</th>\n",
       "      <th>Pressure9am</th>\n",
       "      <th>Pressure3pm</th>\n",
       "      <th>Cloud9am</th>\n",
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       "      <th>Temp9am</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3261</th>\n",
       "      <td>6/16/2017</td>\n",
       "      <td>11.9</td>\n",
       "      <td>17.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.2</td>\n",
       "      <td>WNW</td>\n",
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       "      <td>W</td>\n",
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       "      <td>...</td>\n",
       "      <td>79</td>\n",
       "      <td>69</td>\n",
       "      <td>1026.2</td>\n",
       "      <td>1023.5</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>13.3</td>\n",
       "      <td>17.2</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3262</th>\n",
       "      <td>6/17/2017</td>\n",
       "      <td>13.2</td>\n",
       "      <td>19.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>SSW</td>\n",
       "      <td>26</td>\n",
       "      <td>WNW</td>\n",
       "      <td>SSW</td>\n",
       "      <td>...</td>\n",
       "      <td>81</td>\n",
       "      <td>67</td>\n",
       "      <td>1024.3</td>\n",
       "      <td>1021.8</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>14.6</td>\n",
       "      <td>17.4</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3263</th>\n",
       "      <td>6/18/2017</td>\n",
       "      <td>11.3</td>\n",
       "      <td>18.0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.3</td>\n",
       "      <td>S</td>\n",
       "      <td>52</td>\n",
       "      <td>SW</td>\n",
       "      <td>SSW</td>\n",
       "      <td>...</td>\n",
       "      <td>83</td>\n",
       "      <td>62</td>\n",
       "      <td>1025.7</td>\n",
       "      <td>1025.8</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>12.9</td>\n",
       "      <td>17.6</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3264</th>\n",
       "      <td>6/19/2017</td>\n",
       "      <td>11.2</td>\n",
       "      <td>18.3</td>\n",
       "      <td>0.4</td>\n",
       "      <td>2.2</td>\n",
       "      <td>1.9</td>\n",
       "      <td>SSW</td>\n",
       "      <td>37</td>\n",
       "      <td>W</td>\n",
       "      <td>S</td>\n",
       "      <td>...</td>\n",
       "      <td>79</td>\n",
       "      <td>69</td>\n",
       "      <td>1030.4</td>\n",
       "      <td>1028.4</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>12.7</td>\n",
       "      <td>17.2</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3265</th>\n",
       "      <td>6/20/2017</td>\n",
       "      <td>11.3</td>\n",
       "      <td>20.0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>2.2</td>\n",
       "      <td>5.8</td>\n",
       "      <td>W</td>\n",
       "      <td>26</td>\n",
       "      <td>W</td>\n",
       "      <td>SSW</td>\n",
       "      <td>...</td>\n",
       "      <td>88</td>\n",
       "      <td>60</td>\n",
       "      <td>1028.7</td>\n",
       "      <td>1025.2</td>\n",
       "      <td>6</td>\n",
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       "      <td>11.9</td>\n",
       "      <td>19.7</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
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       "    <tr>\n",
       "      <th>3266</th>\n",
       "      <td>6/21/2017</td>\n",
       "      <td>8.6</td>\n",
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       "      <td>2.0</td>\n",
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       "      <td>52</td>\n",
       "      <td>1025.9</td>\n",
       "      <td>1025.3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>10.5</td>\n",
       "      <td>17.9</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3267</th>\n",
       "      <td>6/22/2017</td>\n",
       "      <td>9.3</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
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       "      <td>W</td>\n",
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       "      <td>78</td>\n",
       "      <td>53</td>\n",
       "      <td>1028.5</td>\n",
       "      <td>1024.6</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>11.0</td>\n",
       "      <td>18.7</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3268</th>\n",
       "      <td>6/23/2017</td>\n",
       "      <td>9.4</td>\n",
       "      <td>17.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.4</td>\n",
       "      <td>2.7</td>\n",
       "      <td>W</td>\n",
       "      <td>24</td>\n",
       "      <td>WNW</td>\n",
       "      <td>N</td>\n",
       "      <td>...</td>\n",
       "      <td>85</td>\n",
       "      <td>56</td>\n",
       "      <td>1020.8</td>\n",
       "      <td>1015.0</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>10.2</td>\n",
       "      <td>17.3</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3269</th>\n",
       "      <td>6/24/2017</td>\n",
       "      <td>10.1</td>\n",
       "      <td>19.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>9.3</td>\n",
       "      <td>W</td>\n",
       "      <td>43</td>\n",
       "      <td>W</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>56</td>\n",
       "      <td>35</td>\n",
       "      <td>1017.3</td>\n",
       "      <td>1015.1</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>12.4</td>\n",
       "      <td>19.0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3270</th>\n",
       "      <td>6/25/2017</td>\n",
       "      <td>7.6</td>\n",
       "      <td>19.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.4</td>\n",
       "      <td>9.4</td>\n",
       "      <td>W</td>\n",
       "      <td>35</td>\n",
       "      <td>W</td>\n",
       "      <td>W</td>\n",
       "      <td>...</td>\n",
       "      <td>73</td>\n",
       "      <td>32</td>\n",
       "      <td>1018.6</td>\n",
       "      <td>1015.4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>9.4</td>\n",
       "      <td>18.8</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 22 columns</p>\n",
       "</div>\n",
       "    <div class=\"colab-df-buttons\">\n",
       "\n",
       "  <div class=\"colab-df-container\">\n",
       "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-4ae53c9b-3934-42b1-8362-19c51af377e3')\"\n",
       "            title=\"Convert this dataframe to an interactive table.\"\n",
       "            style=\"display:none;\">\n",
       "\n",
       "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
       "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
       "  </svg>\n",
       "    </button>\n",
       "\n",
       "  <style>\n",
       "    .colab-df-container {\n",
       "      display:flex;\n",
       "      gap: 12px;\n",
       "    }\n",
       "\n",
       "    .colab-df-convert {\n",
       "      background-color: #E8F0FE;\n",
       "      border: none;\n",
       "      border-radius: 50%;\n",
       "      cursor: pointer;\n",
       "      display: none;\n",
       "      fill: #1967D2;\n",
       "      height: 32px;\n",
       "      padding: 0 0 0 0;\n",
       "      width: 32px;\n",
       "    }\n",
       "\n",
       "    .colab-df-convert:hover {\n",
       "      background-color: #E2EBFA;\n",
       "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
       "      fill: #174EA6;\n",
       "    }\n",
       "\n",
       "    .colab-df-buttons div {\n",
       "      margin-bottom: 4px;\n",
       "    }\n",
       "\n",
       "    [theme=dark] .colab-df-convert {\n",
       "      background-color: #3B4455;\n",
       "      fill: #D2E3FC;\n",
       "    }\n",
       "\n",
       "    [theme=dark] .colab-df-convert:hover {\n",
       "      background-color: #434B5C;\n",
       "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
       "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
       "      fill: #FFFFFF;\n",
       "    }\n",
       "  </style>\n",
       "\n",
       "    <script>\n",
       "      const buttonEl =\n",
       "        document.querySelector('#df-4ae53c9b-3934-42b1-8362-19c51af377e3 button.colab-df-convert');\n",
       "      buttonEl.style.display =\n",
       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
       "\n",
       "      async function convertToInteractive(key) {\n",
       "        const element = document.querySelector('#df-4ae53c9b-3934-42b1-8362-19c51af377e3');\n",
       "        const dataTable =\n",
       "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
       "                                                    [key], {});\n",
       "        if (!dataTable) return;\n",
       "\n",
       "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
       "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
       "          + ' to learn more about interactive tables.';\n",
       "        element.innerHTML = '';\n",
       "        dataTable['output_type'] = 'display_data';\n",
       "        await google.colab.output.renderOutput(dataTable, element);\n",
       "        const docLink = document.createElement('div');\n",
       "        docLink.innerHTML = docLinkHtml;\n",
       "        element.appendChild(docLink);\n",
       "      }\n",
       "    </script>\n",
       "  </div>\n",
       "\n",
       "\n",
       "<div id=\"df-578ff901-ee0d-433a-be76-8e128f432d96\">\n",
       "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-578ff901-ee0d-433a-be76-8e128f432d96')\"\n",
       "            title=\"Suggest charts\"\n",
       "            style=\"display:none;\">\n",
       "\n",
       "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
       "     width=\"24px\">\n",
       "    <g>\n",
       "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
       "    </g>\n",
       "</svg>\n",
       "  </button>\n",
       "\n",
       "<style>\n",
       "  .colab-df-quickchart {\n",
       "      --bg-color: #E8F0FE;\n",
       "      --fill-color: #1967D2;\n",
       "      --hover-bg-color: #E2EBFA;\n",
       "      --hover-fill-color: #174EA6;\n",
       "      --disabled-fill-color: #AAA;\n",
       "      --disabled-bg-color: #DDD;\n",
       "  }\n",
       "\n",
       "  [theme=dark] .colab-df-quickchart {\n",
       "      --bg-color: #3B4455;\n",
       "      --fill-color: #D2E3FC;\n",
       "      --hover-bg-color: #434B5C;\n",
       "      --hover-fill-color: #FFFFFF;\n",
       "      --disabled-bg-color: #3B4455;\n",
       "      --disabled-fill-color: #666;\n",
       "  }\n",
       "\n",
       "  .colab-df-quickchart {\n",
       "    background-color: var(--bg-color);\n",
       "    border: none;\n",
       "    border-radius: 50%;\n",
       "    cursor: pointer;\n",
       "    display: none;\n",
       "    fill: var(--fill-color);\n",
       "    height: 32px;\n",
       "    padding: 0;\n",
       "    width: 32px;\n",
       "  }\n",
       "\n",
       "  .colab-df-quickchart:hover {\n",
       "    background-color: var(--hover-bg-color);\n",
       "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
       "    fill: var(--button-hover-fill-color);\n",
       "  }\n",
       "\n",
       "  .colab-df-quickchart-complete:disabled,\n",
       "  .colab-df-quickchart-complete:disabled:hover {\n",
       "    background-color: var(--disabled-bg-color);\n",
       "    fill: var(--disabled-fill-color);\n",
       "    box-shadow: none;\n",
       "  }\n",
       "\n",
       "  .colab-df-spinner {\n",
       "    border: 2px solid var(--fill-color);\n",
       "    border-color: transparent;\n",
       "    border-bottom-color: var(--fill-color);\n",
       "    animation:\n",
       "      spin 1s steps(1) infinite;\n",
       "  }\n",
       "\n",
       "  @keyframes spin {\n",
       "    0% {\n",
       "      border-color: transparent;\n",
       "      border-bottom-color: var(--fill-color);\n",
       "      border-left-color: var(--fill-color);\n",
       "    }\n",
       "    20% {\n",
       "      border-color: transparent;\n",
       "      border-left-color: var(--fill-color);\n",
       "      border-top-color: var(--fill-color);\n",
       "    }\n",
       "    30% {\n",
       "      border-color: transparent;\n",
       "      border-left-color: var(--fill-color);\n",
       "      border-top-color: var(--fill-color);\n",
       "      border-right-color: var(--fill-color);\n",
       "    }\n",
       "    40% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
       "      border-top-color: var(--fill-color);\n",
       "    }\n",
       "    60% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
       "    }\n",
       "    80% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
       "      border-bottom-color: var(--fill-color);\n",
       "    }\n",
       "    90% {\n",
       "      border-color: transparent;\n",
       "      border-bottom-color: var(--fill-color);\n",
       "    }\n",
       "  }\n",
       "</style>\n",
       "\n",
       "  <script>\n",
       "    async function quickchart(key) {\n",
       "      const quickchartButtonEl =\n",
       "        document.querySelector('#' + key + ' button');\n",
       "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
       "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
       "      try {\n",
       "        const charts = await google.colab.kernel.invokeFunction(\n",
       "            'suggestCharts', [key], {});\n",
       "      } catch (error) {\n",
       "        console.error('Error during call to suggestCharts:', error);\n",
       "      }\n",
       "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
       "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
       "    }\n",
       "    (() => {\n",
       "      let quickchartButtonEl =\n",
       "        document.querySelector('#df-578ff901-ee0d-433a-be76-8e128f432d96 button');\n",
       "      quickchartButtonEl.style.display =\n",
       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
       "    })();\n",
       "  </script>\n",
       "</div>\n",
       "    </div>\n",
       "  </div>\n"
      ],
      "text/plain": [
       "           Date  MinTemp  MaxTemp  Rainfall  Evaporation  Sunshine  \\\n",
       "3261  6/16/2017     11.9     17.3       0.0          1.6       0.2   \n",
       "3262  6/17/2017     13.2     19.1       0.0          1.0       0.2   \n",
       "3263  6/18/2017     11.3     18.0       1.8          2.0       6.3   \n",
       "3264  6/19/2017     11.2     18.3       0.4          2.2       1.9   \n",
       "3265  6/20/2017     11.3     20.0       4.4          2.2       5.8   \n",
       "3266  6/21/2017      8.6     19.6       0.0          2.0       7.8   \n",
       "3267  6/22/2017      9.3     19.2       0.0          2.0       9.2   \n",
       "3268  6/23/2017      9.4     17.7       0.0          2.4       2.7   \n",
       "3269  6/24/2017     10.1     19.3       0.0          1.4       9.3   \n",
       "3270  6/25/2017      7.6     19.3       0.0          3.4       9.4   \n",
       "\n",
       "     WindGustDir  WindGustSpeed WindDir9am WindDir3pm  ...  Humidity9am  \\\n",
       "3261         WNW             26          W        WSW  ...           79   \n",
       "3262         SSW             26        WNW        SSW  ...           81   \n",
       "3263           S             52         SW        SSW  ...           83   \n",
       "3264         SSW             37          W          S  ...           79   \n",
       "3265           W             26          W        SSW  ...           88   \n",
       "3266         SSE             37          W        SSE  ...           73   \n",
       "3267           W             30          W        ESE  ...           78   \n",
       "3268           W             24        WNW          N  ...           85   \n",
       "3269           W             43          W          W  ...           56   \n",
       "3270           W             35          W          W  ...           73   \n",
       "\n",
       "      Humidity3pm  Pressure9am  Pressure3pm  Cloud9am  Cloud3pm  Temp9am  \\\n",
       "3261           69       1026.2       1023.5         7         7     13.3   \n",
       "3262           67       1024.3       1021.8         7         7     14.6   \n",
       "3263           62       1025.7       1025.8         3         5     12.9   \n",
       "3264           69       1030.4       1028.4         6         7     12.7   \n",
       "3265           60       1028.7       1025.2         6         1     11.9   \n",
       "3266           52       1025.9       1025.3         2         2     10.5   \n",
       "3267           53       1028.5       1024.6         2         2     11.0   \n",
       "3268           56       1020.8       1015.0         6         6     10.2   \n",
       "3269           35       1017.3       1015.1         5         2     12.4   \n",
       "3270           32       1018.6       1015.4         1         1      9.4   \n",
       "\n",
       "      Temp3pm  RainToday  RainTomorrow  \n",
       "3261     17.2         No            No  \n",
       "3262     17.4         No           Yes  \n",
       "3263     17.6        Yes            No  \n",
       "3264     17.2         No           Yes  \n",
       "3265     19.7        Yes            No  \n",
       "3266     17.9         No            No  \n",
       "3267     18.7         No            No  \n",
       "3268     17.3         No            No  \n",
       "3269     19.0         No            No  \n",
       "3270     18.8         No            No  \n",
       "\n",
       "[10 rows x 22 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "09f6a14a-c5ad-496f-96d5-71daaee65471",
   "metadata": {
    "id": "09f6a14a-c5ad-496f-96d5-71daaee65471"
   },
   "source": [
    "The `df.tail()` function in Python, when used with a DataFrame object from the `pandas` library, returns the last **n** rows of the DataFrame. This is useful for quickly verifying data, especially after sorting or appending rows. By default, if no parameter is specified, `df.tail()` will return the last **5** rows. You can specify the number of rows you want to display by passing an integer as an argument, like `df.tail(10)` to display the last 10 rows"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "73103c75-dd72-4ce7-a7df-bc607e6c8d6b",
   "metadata": {
    "id": "73103c75-dd72-4ce7-a7df-bc607e6c8d6b"
   },
   "source": [
    "## `df.info()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "dbfb25ac",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "dbfb25ac",
    "outputId": "714d9c02-4cd2-49f8-e4b4-da80bdd00722"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 3271 entries, 0 to 3270\n",
      "Data columns (total 22 columns):\n",
      " #   Column         Non-Null Count  Dtype  \n",
      "---  ------         --------------  -----  \n",
      " 0   Date           3271 non-null   object \n",
      " 1   MinTemp        3271 non-null   float64\n",
      " 2   MaxTemp        3271 non-null   float64\n",
      " 3   Rainfall       3271 non-null   float64\n",
      " 4   Evaporation    3271 non-null   float64\n",
      " 5   Sunshine       3271 non-null   float64\n",
      " 6   WindGustDir    3271 non-null   object \n",
      " 7   WindGustSpeed  3271 non-null   int64  \n",
      " 8   WindDir9am     3271 non-null   object \n",
      " 9   WindDir3pm     3271 non-null   object \n",
      " 10  WindSpeed9am   3271 non-null   int64  \n",
      " 11  WindSpeed3pm   3271 non-null   int64  \n",
      " 12  Humidity9am    3271 non-null   int64  \n",
      " 13  Humidity3pm    3271 non-null   int64  \n",
      " 14  Pressure9am    3271 non-null   float64\n",
      " 15  Pressure3pm    3271 non-null   float64\n",
      " 16  Cloud9am       3271 non-null   int64  \n",
      " 17  Cloud3pm       3271 non-null   int64  \n",
      " 18  Temp9am        3271 non-null   float64\n",
      " 19  Temp3pm        3271 non-null   float64\n",
      " 20  RainToday      3271 non-null   object \n",
      " 21  RainTomorrow   3271 non-null   object \n",
      "dtypes: float64(9), int64(7), object(6)\n",
      "memory usage: 562.3+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0cc74df-b677-40e2-896e-a01763b729eb",
   "metadata": {
    "id": "b0cc74df-b677-40e2-896e-a01763b729eb"
   },
   "source": [
    "The `df.info()` method in Python, when used with a DataFrame object from the `pandas` library, prints a concise summary of the DataFrame. This summary includes information such as the index dtype, column dtypes, non-null values, and memory usage. It’s a valuable method for getting a quick overview of the DataFrame, especially to understand its structure, the data types of each column, and to identify columns with missing values"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a1566358-b679-4bb2-9cb7-166b5f8c1fad",
   "metadata": {
    "id": "a1566358-b679-4bb2-9cb7-166b5f8c1fad"
   },
   "source": [
    "## `df.columns`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b2c962b2-062e-4efa-aa96-c2baef12883c",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "b2c962b2-062e-4efa-aa96-c2baef12883c",
    "outputId": "bd99522c-15ff-4887-c8c3-9bfd2b9ce75a"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Date', 'MinTemp', 'MaxTemp', 'Rainfall', 'Evaporation', 'Sunshine',\n",
       "       'WindGustDir', 'WindGustSpeed', 'WindDir9am', 'WindDir3pm',\n",
       "       'WindSpeed9am', 'WindSpeed3pm', 'Humidity9am', 'Humidity3pm',\n",
       "       'Pressure9am', 'Pressure3pm', 'Cloud9am', 'Cloud3pm', 'Temp9am',\n",
       "       'Temp3pm', 'RainToday', 'RainTomorrow'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "746fa2f9",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "746fa2f9",
    "outputId": "1c48cf85-ce99-4186-8281-86b68c677d04"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['Date', 'MinTemp', 'MaxTemp', 'Rainfall', 'Evaporation', 'Sunshine',\n",
      "       'WindGustDir', 'WindGustSpeed', 'WindDir9am', 'WindDir3pm',\n",
      "       'WindSpeed9am', 'WindSpeed3pm', 'Humidity9am', 'Humidity3pm',\n",
      "       'Pressure9am', 'Pressure3pm', 'Cloud9am', 'Cloud3pm', 'Temp9am',\n",
      "       'Temp3pm', 'RainToday', 'RainTomorrow'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "print(df.columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3bc2dc7a-4d56-40aa-b992-bd9b9d324b75",
   "metadata": {
    "id": "3bc2dc7a-4d56-40aa-b992-bd9b9d324b75"
   },
   "source": [
    "The `df.columns` attribute in Python, when used with a DataFrame object from the `pandas` library, returns the column labels of the DataFrame as an Index object. This attribute is useful for viewing the column names, modifying them, or using them in further analysis and data manipulation tasks"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c0e73512-3976-4272-861f-2f988db61c9c",
   "metadata": {
    "id": "c0e73512-3976-4272-861f-2f988db61c9c"
   },
   "source": [
    "## `df.shape`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "63ad9e25-afaf-49cb-95a6-80c56c863b50",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "63ad9e25-afaf-49cb-95a6-80c56c863b50",
    "outputId": "dfa48c29-3851-40bf-9f93-0d8108f1e81a"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3271, 22)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "db47cbfc",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "db47cbfc",
    "outputId": "1525d37a-ef39-4802-9d17-42838f26aad2"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(3271, 22)\n"
     ]
    }
   ],
   "source": [
    "print(df.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ad007d0-8774-403f-bdfe-b3d531e19d84",
   "metadata": {
    "id": "0ad007d0-8774-403f-bdfe-b3d531e19d84"
   },
   "source": [
    "The `df.shape` attribute in Python, when used with a DataFrame object from the `pandas` library, returns a tuple representing the dimensionality of the DataFrame. This tuple contains two elements: the number of rows and the number of columns. It does not require parentheses because it is an attribute, not a method"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9d1179f0-4347-42b3-9d3a-300f99583fcd",
   "metadata": {
    "id": "9d1179f0-4347-42b3-9d3a-300f99583fcd"
   },
   "source": [
    "# My First plot!!! (Introduction to Matplotlib)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c33f9b4f",
   "metadata": {
    "id": "c33f9b4f"
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f6a9c2de",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 472
    },
    "id": "f6a9c2de",
    "outputId": "292d5a0e-9401-4a23-fac9-cfa4a225d765"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x=np.linspace(0,10)\n",
    "y= x**2\n",
    "plt.plot(x,y,'red')\n",
    "plt.xlabel('X-axis label')\n",
    "plt.ylabel('Y-axis label')\n",
    "plt.title('My First plot')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "57ae8569-0e8d-4328-9309-69a0e66d4c8e",
   "metadata": {
    "id": "57ae8569-0e8d-4328-9309-69a0e66d4c8e",
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "## `np.linspace`\n",
    "The `np.linspace` function in Python, provided by the NumPy library, is used to create an array of evenly spaced numbers over a specified interval. The function returns `num` evenly spaced samples, calculated over the interval `[start, stop]`. The endpoint of the interval can optionally be excluded.\n",
    "## `plt.plot`\n",
    "The `plt.plot` function in Python is a versatile command from the Matplotlib library used to create a variety of plots, including line plots. When you call `plt.plot`, you can specify the data points you want to plot, the type of plot you want, and various formatting options like color, marker style, and line style.\n",
    "## `plt.xlabel`\n",
    "The `plt.xlabel` function in Matplotlib’s Pyplot module is used to set the label for the x-axis of a plot.\n",
    "## `plt.ylabel`\n",
    "The `plt.ylabel` function in Matplotlib’s Pyplot module is used to set the label for the y-axis of a plot.\n",
    "## `plt.title`\n",
    "The `plt.title` function in Matplotlib’s Pyplot module is used to set the title of a plot. The title is displayed above the plot.\n",
    "## `plt.show()`\n",
    "The `plt.show()` function in Python, which is part of the Matplotlib library, is used to display all figures and block until the figures have been closed. When you use Matplotlib to plot graphs, the figures are not displayed until you call `plt.show()`. This function will open a window with the graph and wait for any user interactions if the program is not running in an interactive mode."
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    "# Conclusion\n",
    "Python libraries are a testament to the language’s versatility and the collaborative spirit of the programming community. These libraries are just the tip of the iceberg in Python’s vast repository of resources. Whether you’re manipulating multi-dimensional arrays with `Xarray`, building machine learning models with `Scikit-learn`, creating beautiful visualizations with `Seaborn`, or processing geospatial data with `OSGeo`, Python has a library for almost every need. They simplify complex tasks, promote code reuse, and enable programmers to stand on the shoulders of giants. Remember, `pip` is a powerful tool that simplifies the process of managing Python packages. *Happy coding!*"
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