From ff0c4d4865e91c449ec0dcf9ee6d4357093fa754 Mon Sep 17 00:00:00 2001 From: Suyash Shekhar Date: Sat, 6 Oct 2018 03:15:57 +0800 Subject: [PATCH 01/14] Change pandas Timestamp import --- ggplot/stats/smoothers.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ggplot/stats/smoothers.py b/ggplot/stats/smoothers.py index 5a8fbf37..88883044 100644 --- a/ggplot/stats/smoothers.py +++ b/ggplot/stats/smoothers.py @@ -1,7 +1,7 @@ from __future__ import (absolute_import, division, print_function, unicode_literals) import numpy as np -from pandas.lib import Timestamp +from pandas import Timestamp import pandas as pd import statsmodels.api as sm from statsmodels.nonparametric.smoothers_lowess import lowess as smlowess From 9eb2d8c6fb2e67aa66b238272f48e1495086af6d Mon Sep 17 00:00:00 2001 From: Suyash Shekhar Date: Sat, 6 Oct 2018 03:18:47 +0800 Subject: [PATCH 02/14] Fix incompatibility with pandas 0.20.0 --- ggplot/stats/smoothers.py | 2 +- ggplot/utils.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/ggplot/stats/smoothers.py b/ggplot/stats/smoothers.py index 88883044..2198a3f8 100644 --- a/ggplot/stats/smoothers.py +++ b/ggplot/stats/smoothers.py @@ -11,7 +11,7 @@ import datetime date_types = ( - pd.tslib.Timestamp, + pd.Timestamp, pd.DatetimeIndex, pd.Period, pd.PeriodIndex, diff --git a/ggplot/utils.py b/ggplot/utils.py index d0d5dfb6..6c9a92f7 100644 --- a/ggplot/utils.py +++ b/ggplot/utils.py @@ -78,7 +78,7 @@ def is_iterable(obj): return False date_types = ( - pd.tslib.Timestamp, + pd.Timestamp, pd.DatetimeIndex, pd.Period, pd.PeriodIndex, From cd8f4418de444ad0543c29f3ccaca460c92d2383 Mon Sep 17 00:00:00 2001 From: Suyash Shekhar Date: Sat, 6 Oct 2018 04:02:07 +0800 Subject: [PATCH 03/14] Make save_as_base64 Python 3 compatible --- ggplot/ggplot.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/ggplot/ggplot.py b/ggplot/ggplot.py index ba12a6bd..714b3f44 100755 --- a/ggplot/ggplot.py +++ b/ggplot/ggplot.py @@ -570,10 +570,10 @@ def save_as_base64(self, as_tag=False, width=None, height=None, dpi=180): height: int, float height of the plot in inches """ - imgdata = six.StringIO() + imgdata = six.BytesIO() self.save(imgdata, width=width, height=height, dpi=dpi) imgdata.seek(0) # rewind the data - uri = 'data:image/png;base64,' + urllib.quote(base64.b64encode(imgdata.buf)) + uri = 'data:image/png;base64,' + urllib.quote(base64.b64encode(imgdata.read())) if as_tag==True: return '' % uri else: From 33376f8c44128a9f22546c99b16966e2850c06ee Mon Sep 17 00:00:00 2001 From: Suyash Shekhar Date: Sat, 6 Oct 2018 04:04:34 +0800 Subject: [PATCH 04/14] Handle pandas sort for different versions --- ggplot/ggplot.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/ggplot/ggplot.py b/ggplot/ggplot.py index 714b3f44..c1ba4bc9 100755 --- a/ggplot/ggplot.py +++ b/ggplot/ggplot.py @@ -599,7 +599,10 @@ def _prep_layer_for_plotting(self, layer, facetgroup): if 'fill' in self._aes: fillcol_raw = self._aes['fill'][:-5] fillcol = self._aes['fill'] - fill_levels = self.data[[fillcol_raw, fillcol]].sort(fillcol_raw)[fillcol].unique() + try: # change in Pandas-0.19 + fill_levels = self.data[[fillcol_raw, fillcol]].sort_values(by=fillcol_raw)[fillcol].unique() + except: # before Pandas-0.19 + fill_levels = self.data[[fillcol_raw, fillcol]].sort(fillcol_raw)[fillcol].unique() else: fill_levels = None return dict(x_levels=self.data[self._aes['x']].unique(), fill_levels=fill_levels, lookups=df) From 859fc88b8cc25c1aed91e117343fba418c77d6f5 Mon Sep 17 00:00:00 2001 From: nabaskes Date: Fri, 12 Oct 2018 12:45:54 -0400 Subject: [PATCH 05/14] fixed broken qplot label --- ggplot/qplot.py | 23 ++++++++++------------- 1 file changed, 10 insertions(+), 13 deletions(-) diff --git a/ggplot/qplot.py b/ggplot/qplot.py index 9ef231d6..24bd58a5 100644 --- a/ggplot/qplot.py +++ b/ggplot/qplot.py @@ -7,13 +7,11 @@ from .geoms import geom_point, geom_bar, geom_histogram, geom_line # , geom_boxplot from .scales.scale_log import scale_x_log, scale_y_log import pandas as pd -import numpy as np import six - def qplot(x, y=None, color=None, size=None, fill=None, data=None, - geom="auto", stat=[], position=[], xlim=None, ylim=None, log="", - main=None, xlab=None, ylab="", asp=None): + geom="auto", stat=[], position=[], xlim=None, ylim=None, log="", + main=None, xlabel=None, ylabel="", asp=None): """ Parameters ---------- @@ -43,9 +41,9 @@ def qplot(x, y=None, color=None, size=None, fill=None, data=None, which variables to log transform ("x", "y", or "xy") main: string title for the plot - xlab: string + xlabel: string title for the x axis - ylab: string + ylabel: string title for the y axis asp: string the y/x aspect ratio @@ -69,8 +67,8 @@ def qplot(x, y=None, color=None, size=None, fill=None, data=None, >>> print qplot('mpg', data=mtcars, geom="hist", main="hist") >>> print qplot('mpg', data=mtcars, geom="histogram", main="histogram") >>> print qplot('cyl', 'mpg', data=mtcars, geom="bar", main="bar") - >>> print qplot('mpg', 'drat', data=mtcars, xlab= "x lab", main="xlab") - >>> print qplot('mpg', 'drat', data=mtcars, ylab = "y lab", main="ylab") + >>> print qplot('mpg', 'drat', data=mtcars, xlabel= "x lab", main="xlab") + >>> print qplot('mpg', 'drat', data=mtcars, ylabel = "y lab", main="ylab") """ if x is not None and not isinstance(x, six.string_types): @@ -80,7 +78,6 @@ def qplot(x, y=None, color=None, size=None, fill=None, data=None, data['y'] = y y = 'y' - aes_elements = {"x": x} if y: aes_elements["y"] = y @@ -114,10 +111,10 @@ def qplot(x, y=None, color=None, size=None, fill=None, data=None, p += scale_x_log() if "y" in log: p += scale_y_log() - if xlab: - p += xlabel(xlab) - if ylab: - p += ylabel(ylab) + if xlabel: + p += xlab(xlabel) + if ylabel: + p += ylab(ylabel) if main: p += ggtitle(main) return p From 0268fa008635774864155b1da2c14513db5d394b Mon Sep 17 00:00:00 2001 From: Suyash Shekhar Date: Sun, 14 Oct 2018 13:28:19 +0800 Subject: [PATCH 06/14] Update README.md --- README.md | 45 +++++++++++++-------------------------------- 1 file changed, 13 insertions(+), 32 deletions(-) diff --git a/README.md b/README.md index 5167fa96..5fd9b321 100644 --- a/README.md +++ b/README.md @@ -1,9 +1,18 @@ -# ggplot +# ggplot - a maintained fork - - +## Why this fork? +`ggplot` is no longer maintained by its owner and still has a bunch of issues which remain unsolved. Some of these include incompatibility with newer versions of `pandas` and Python 3. -### What is it? +Many projects still rely on `ggplot` and so here is a working copy of `ggplot` which is readily maintained and is open to updates and fixes. + +## Installation + +```bash +$ pip3 install git+https://github.com/sushinoya/ggpy +``` + + +## What is ggpy? `ggplot` is a Python implementation of the grammar of graphics. It is not intended to be a feature-for-feature port of [`ggplot2 for R`](https://github.com/hadley/ggplot2)--though there is much greatness in `ggplot2`, the Python world could stand to benefit @@ -19,31 +28,3 @@ ggplot(diamonds, aes(x='price', color='clarity')) + \ facet_wrap('cut') ``` ![](./docs/example.png) - -### Installation -```bash -$ pip install -U ggplot -# or -$ conda install -c conda-forge ggplot -# or -pip install git+https://github.com/yhat/ggplot.git -``` - -### Examples -Examples are the best way to learn. There is a Jupyter Notebook full of them. -There are also notebooks that show how to do particular things with ggplot -(i.e. [make a scatter plot](./docs/how-to/Making%20a%20Scatter%20Plot.ipynb) or [make a histogram](./docs/how-to/Making%20a%20Scatter%20Plot.ipynb)). - -- [docs](./docs) -- [gallery](./docs/Gallery.ipynb) -- [various examples](./examples.md) - - -### What happened to the old version that didn't work? -It's gone--the windows, the doors, [everything](https://www.youtube.com/watch?v=YuxCKv_0GZc). -Just kidding, [you can find it here](https://github.com/yhat/ggplot/tree/v0.6.6), though I'm not sure why you'd want to look at it. The data grouping and manipulation bits were re-written -(so they actually worked) with things like facets in mind. - -### Contributing -Thanks to all of the ggplot [contributors](./contributors.md#contributors)! -See *[contributing.md](./contributing.md)*. From 6df245925d5c1984b0156c6294c94404dd85a095 Mon Sep 17 00:00:00 2001 From: nabaskes Date: Mon, 15 Oct 2018 11:36:36 -0400 Subject: [PATCH 07/14] PEP8 compliance --- ggplot/qplot.py | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/ggplot/qplot.py b/ggplot/qplot.py index 24bd58a5..da062509 100644 --- a/ggplot/qplot.py +++ b/ggplot/qplot.py @@ -9,9 +9,10 @@ import pandas as pd import six + def qplot(x, y=None, color=None, size=None, fill=None, data=None, - geom="auto", stat=[], position=[], xlim=None, ylim=None, log="", - main=None, xlabel=None, ylabel="", asp=None): + geom="auto", stat=[], position=[], xlim=None, ylim=None, log="", + main=None, xlabel=None, ylabel="", asp=None): """ Parameters ---------- @@ -67,8 +68,8 @@ def qplot(x, y=None, color=None, size=None, fill=None, data=None, >>> print qplot('mpg', data=mtcars, geom="hist", main="hist") >>> print qplot('mpg', data=mtcars, geom="histogram", main="histogram") >>> print qplot('cyl', 'mpg', data=mtcars, geom="bar", main="bar") - >>> print qplot('mpg', 'drat', data=mtcars, xlabel= "x lab", main="xlab") - >>> print qplot('mpg', 'drat', data=mtcars, ylabel = "y lab", main="ylab") + >>> print qplot('mpg', 'drat', data=mtcars, xlabel="x lab", main="xlab") + >>> print qplot('mpg', 'drat', data=mtcars, ylabel="y lab", main="ylab") """ if x is not None and not isinstance(x, six.string_types): From 0e8cd0f8ed3052223def6bab240235c751be2024 Mon Sep 17 00:00:00 2001 From: Suyash Shekhar Date: Wed, 17 Oct 2018 20:07:07 +0800 Subject: [PATCH 08/14] Update README.md --- README.md | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index 5fd9b321..f215fd1d 100644 --- a/README.md +++ b/README.md @@ -1,17 +1,17 @@ -# ggplot - a maintained fork +# ggplot - a working, maintained fork ## Why this fork? -`ggplot` is no longer maintained by its owner and still has a bunch of issues which remain unsolved. Some of these include incompatibility with newer versions of `pandas` and Python 3. +`ggplot` is a great python library. However, it is no longer maintained by its owner and still has a bunch of issues which remain unsolved. Some of these include incompatibility with newer versions of `pandas` and Python 3. -Many projects still rely on `ggplot` and so here is a working copy of `ggplot` which is readily maintained and is open to updates and fixes. +Many projects still rely on `ggplot` and many have to either move to alternatives or manually update `ggpy`'s code after installing it to fix compatibility issues. To get a better context of the issue you can refer to [#654 Is this project dead?](https://github.com/yhat/ggpy/issues/654) -## Installation +This fork is a working copy of `ggplot` which is readily maintained and is open to updates and fixes so that developers do not have to make fixes manually. +## Installation ```bash $ pip3 install git+https://github.com/sushinoya/ggpy ``` - ## What is ggpy? `ggplot` is a Python implementation of the grammar of graphics. It is not intended to be a feature-for-feature port of [`ggplot2 for R`](https://github.com/hadley/ggplot2)--though From 7ec7b5274280560c291fcf898762c8018fdd7710 Mon Sep 17 00:00:00 2001 From: nabaskes Date: Wed, 17 Oct 2018 11:23:46 -0400 Subject: [PATCH 09/14] added plot limits to qplot + style --- ggplot/chart_components.py | 4 ++-- ggplot/qplot.py | 16 ++++++++++------ 2 files changed, 12 insertions(+), 8 deletions(-) diff --git a/ggplot/chart_components.py b/ggplot/chart_components.py index dacae6c6..723b9cb8 100644 --- a/ggplot/chart_components.py +++ b/ggplot/chart_components.py @@ -82,8 +82,8 @@ class ylim(object): -------- >>> ggplot(mpg, aes(x='hwy')) + geom_hisotgram() + ylim(0, 5) """ - def __init__(self, low = None, high = None): - if low != None : + def __init__(self, low=None, high=None): + if low is not None: try: _ = low - 0 except TypeError: diff --git a/ggplot/qplot.py b/ggplot/qplot.py index da062509..13b0f325 100644 --- a/ggplot/qplot.py +++ b/ggplot/qplot.py @@ -3,15 +3,15 @@ from .ggplot import ggplot from .aes import aes -from .chart_components import ggtitle, xlim, ylim, xlab, ylab, labs -from .geoms import geom_point, geom_bar, geom_histogram, geom_line # , geom_boxplot +from .chart_components import ggtitle, xlim, ylim, xlab, ylab +from .geoms import geom_point, geom_bar, geom_histogram, geom_line #geom_boxplot from .scales.scale_log import scale_x_log, scale_y_log import pandas as pd import six def qplot(x, y=None, color=None, size=None, fill=None, data=None, - geom="auto", stat=[], position=[], xlim=None, ylim=None, log="", + geom="auto", stat=[], position=[], xlimit=None, ylimit=None, log="", main=None, xlabel=None, ylabel="", asp=None): """ Parameters @@ -34,9 +34,9 @@ def qplot(x, y=None, color=None, size=None, fill=None, data=None, specifies which statistics to use position: list gives position adjustment to use - xlim: tuple + xlimit: tuple limits on x axis; i.e. (0, 10) - ylim: tuple, None + ylimit: tuple, None limits on y axis; i.e. (0, 10) log: string which variables to log transform ("x", "y", or "xy") @@ -99,7 +99,7 @@ def qplot(x, y=None, color=None, size=None, fill=None, data=None, "point": geom_point, } # taking our best guess - if geom=="auto": + if geom == "auto": if y is None: geom = geom_histogram else: @@ -116,6 +116,10 @@ def qplot(x, y=None, color=None, size=None, fill=None, data=None, p += xlab(xlabel) if ylabel: p += ylab(ylabel) + if xlimit: + p += xlim(*tuple(xlimit)) + if ylimit: + p += ylim(*tuple(ylimit)) if main: p += ggtitle(main) return p From afcb02dcfa302df15f13b700874766ebcb59f44e Mon Sep 17 00:00:00 2001 From: Samuel Marks <807580+SamuelMarks@users.noreply.github.com> Date: Mon, 10 Jun 2019 01:35:37 +1000 Subject: [PATCH 10/14] [*.py] Upgrade to latest version of pandas; `from __future__ import print_function` for Python 2/3 print compatibility; [.gitignore] Ignore .idea (JetBrains) --- .gitignore | 1 + ggplot/aes.py | 5 +- ggplot/chart_components.py | 4 +- ggplot/geoms/geom_bar.py | 4 +- ggplot/ggplot.py | 2 +- ggplot/stats/smoothers.py | 2 +- ggplot/themes/element_text.py | 2 - ggplot/utils.py | 25 +++-- tests/compare_runs.py | 7 +- tests/facet_tests.py | 3 +- tests/legendtest.py | 13 +-- tests/test_aes_in_geom.py | 4 +- tests/test_area.py | 4 +- tests/test_art.py | 4 +- tests/test_bar.py | 35 +++---- tests/test_boxplot.py | 9 +- tests/test_element_text.py | 5 +- tests/test_error_messages.py | 3 +- tests/test_facet_scales.py | 14 +-- tests/test_facets.py | 9 +- tests/test_geom_errorbar.py | 4 +- tests/test_geom_histogram.py | 6 +- tests/test_geom_polygon.py | 9 +- tests/test_index.py | 3 +- tests/test_line.py | 5 +- tests/test_multiple_lines_489.py | 5 +- tests/test_point.py | 4 +- tests/test_rect.py | 9 +- tests/test_scale.py | 8 +- tests/test_stat_smooth.py | 5 +- tests/test_step.py | 10 +- tests/test_text.py | 6 +- tests/test_tile.py | 5 +- tests/test_unicode.py | 4 +- tests/test_violin.py | 6 +- tests/test_visual.py | 6 +- tests/tests.py | 170 ++++++++++++++++--------------- tests/tests_nan.py | 13 +-- 38 files changed, 229 insertions(+), 204 deletions(-) diff --git a/.gitignore b/.gitignore index 71e60b8a..44ae04d9 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,4 @@ +.idea *.pyc *.swp *.DS_Store diff --git a/ggplot/aes.py b/ggplot/aes.py index 495b2265..f5ce220d 100755 --- a/ggplot/aes.py +++ b/ggplot/aes.py @@ -8,11 +8,10 @@ from patsy.eval import EvalEnvironment -from . import utils - import numpy as np import pandas as pd + class aes(UserDict): """ Creates a dictionary that is used to evaluate @@ -72,7 +71,7 @@ def __init__(self, *args, **kwargs): self.__eval_env__ = EvalEnvironment.capture(1) def __deepcopy__(self, memo): - '''deepcopy support for ggplot''' + """deepcopy support for ggplot""" result = aes() for key, item in self.__dict__.items(): # don't make a deepcopy of the env! diff --git a/ggplot/chart_components.py b/ggplot/chart_components.py index dacae6c6..6d82f3f0 100644 --- a/ggplot/chart_components.py +++ b/ggplot/chart_components.py @@ -140,7 +140,7 @@ class ylab(object): Examples -------- - >>> ggplot(mpg, aes(x='hwy')) + geom_hisotgram() + ylab("Count\n(# of cars)") + >>> ggplot(mpg, aes(x='hwy')) + geom_hisotgram() + ylab('''Count\n(# of cars)''') """ def __init__(self, ylab): if ylab is None: @@ -169,7 +169,7 @@ class labs(object): Examples -------- - >>> ggplot(mpg, aes(x='hwy')) + geom_hisotgram() + labs("Miles / gallon", "Count\n(# of cars)", "MPG Plot") + >>> ggplot(mpg, aes(x='hwy')) + geom_hisotgram() + labs("Miles / gallon", '''Count\n(# of cars)''', "MPG Plot") """ def __init__(self, x=None, y=None, title=None): self.x = x diff --git a/ggplot/geoms/geom_bar.py b/ggplot/geoms/geom_bar.py index 07a62fdd..1be8224b 100755 --- a/ggplot/geoms/geom_bar.py +++ b/ggplot/geoms/geom_bar.py @@ -111,13 +111,13 @@ def plot(self, ax, data, _aes, x_levels, fill_levels, lookups): height = 1.0 ypos = 0 else: - mask = (lookups[variables['x']]==x_level) & (lookups[variables['fill']]==fillval) + mask = (lookups[variables['x']]==x_level) & (lookups[variables['fill']] == fillval) height = lookups[mask]['__calc_weight__'].sum() mask = (lookups[variables['x']]==x_level) & (lookups[variables['fill']] < fillval) ypos = lookups[mask]['__calc_weight__'].sum() else: if fill_levels is not None: - dodge = (width * fill_idx) + dodge = width * fill_idx else: dodge = width ypos = 0.0 diff --git a/ggplot/ggplot.py b/ggplot/ggplot.py index ba12a6bd..98707f7d 100755 --- a/ggplot/ggplot.py +++ b/ggplot/ggplot.py @@ -574,7 +574,7 @@ def save_as_base64(self, as_tag=False, width=None, height=None, dpi=180): self.save(imgdata, width=width, height=height, dpi=dpi) imgdata.seek(0) # rewind the data uri = 'data:image/png;base64,' + urllib.quote(base64.b64encode(imgdata.buf)) - if as_tag==True: + if as_tag: return '' % uri else: return uri diff --git a/ggplot/stats/smoothers.py b/ggplot/stats/smoothers.py index 5a8fbf37..cb18135a 100644 --- a/ggplot/stats/smoothers.py +++ b/ggplot/stats/smoothers.py @@ -11,7 +11,7 @@ import datetime date_types = ( - pd.tslib.Timestamp, + pd.Timestamp, pd.DatetimeIndex, pd.Period, pd.PeriodIndex, diff --git a/ggplot/themes/element_text.py b/ggplot/themes/element_text.py index 785d22ea..56be88cf 100644 --- a/ggplot/themes/element_text.py +++ b/ggplot/themes/element_text.py @@ -1,8 +1,6 @@ from __future__ import (absolute_import, division, print_function, unicode_literals) -from matplotlib.text import Text - FACES = ["plain", "italic", "bold", "bold.italic"] class element_text(object): diff --git a/ggplot/utils.py b/ggplot/utils.py index d0d5dfb6..16970273 100644 --- a/ggplot/utils.py +++ b/ggplot/utils.py @@ -1,21 +1,21 @@ from __future__ import (absolute_import, division, print_function, unicode_literals) +import datetime import matplotlib.cbook as cbook import numpy as np import pandas as pd -import datetime def format_ticks(ticks): are_ints = True for t in ticks: try: - if int(t)!=t: + if int(t) != t: are_ints = False except: return ticks - if are_ints==True: + if are_ints: return [int(t) for t in ticks] return ticks @@ -59,16 +59,11 @@ def is_categorical(obj): - booleans """ try: - float(obj.iloc[0]) - return False + k = float(obj.iloc[0]) + return is_sequence_of_strings(k) or is_sequence_of_booleans(k) except: return True - if is_sequence_of_strings(obj): - return True - if is_sequence_of_booleans(obj): - return True - return False def is_iterable(obj): try: @@ -77,8 +72,9 @@ def is_iterable(obj): except: return False + date_types = ( - pd.tslib.Timestamp, + pd.Timestamp, pd.DatetimeIndex, pd.Period, pd.PeriodIndex, @@ -86,17 +82,20 @@ def is_iterable(obj): datetime.time ) + def is_date(x): return isinstance(x, date_types) + def calc_n_bins(series): - "https://en.wikipedia.org/wiki/Histogram#Number_of_bins_and_width" - q75, q25 = np.percentile(series, [75 , 25]) + """https://en.wikipedia.org/wiki/Histogram#Number_of_bins_and_width""" + q75, q25 = np.percentile(series, [75, 25]) iqr = q75 - q25 h = (2 * iqr) / (len(series)**(1/3.)) k = (series.max() - series.min()) / h return k + def sorted_unique(series): """Return the unique values of *series*, correctly sorted.""" # This handles Categorical data types, which sorted(series.unique()) fails diff --git a/tests/compare_runs.py b/tests/compare_runs.py index b778aa5c..50d3eed7 100644 --- a/tests/compare_runs.py +++ b/tests/compare_runs.py @@ -1,5 +1,7 @@ +from __future__ import print_function import os import sys + import imgdiff import tempfile import operator @@ -7,6 +9,9 @@ from PIL import Image import pandas as pd +if sys.version[0] == 3: + from functools import reduce + rundir1 = sys.argv[1] rundir2 = sys.argv[2] html = """ @@ -59,4 +64,4 @@ def calc_mse(image1, image2): html += "\n" + "
" + pd.DataFrame(table)[['name', 'mse']].to_html(classes='table table-bordered') + "
\n" html += test_results html += "\n" -print html +print(html) diff --git a/tests/facet_tests.py b/tests/facet_tests.py index 7ac0c364..e8dfde47 100644 --- a/tests/facet_tests.py +++ b/tests/facet_tests.py @@ -1,3 +1,4 @@ +from __future__ import print_function from ggplot import * import pandas as pd @@ -6,4 +7,4 @@ # print ggplot(diamonds, aes(x='price')) + geom_histogram() + facet_wrap('cut') -print ggplot(diamonds, aes(x='price', color='factor(cyl)')) + geom_boxplot() +print(ggplot(diamonds, aes(x='price', color='factor(cyl)')) + geom_boxplot()) diff --git a/tests/legendtest.py b/tests/legendtest.py index 2067febe..9946baba 100644 --- a/tests/legendtest.py +++ b/tests/legendtest.py @@ -1,3 +1,4 @@ +from __future__ import print_function from ggplot import * import pandas as pd @@ -7,12 +8,12 @@ mtcars['newcol'] = ["steelblue" if i%2==0 else "coral" for i in range(len(mtcars))] -print ggplot(mtcars, aes(x='mpg', fill='newcol')) + geom_histogram() + scale_fill_identity() -print ggplot(mtcars, aes(x='wt', y='mpg', color='newcol', shape='newcol')) + geom_point() -print ggplot(mtcars, aes(x='mpg', y='wt')) + geom_point(color='royalblue') -print ggplot(mtcars, aes(x='mpg', fill='factor(cyl)')) + geom_bar() -print ggplot(mtcars, aes(x='mpg', y='wt', group='newcol')) + geom_line() +print(ggplot(mtcars, aes(x='mpg', fill='newcol')) + geom_histogram() + scale_fill_identity()) +print(ggplot(mtcars, aes(x='wt', y='mpg', color='newcol', shape='newcol')) + geom_point()) +print(ggplot(mtcars, aes(x='mpg', y='wt')) + geom_point(color='royalblue')) +print(ggplot(mtcars, aes(x='mpg', fill='factor(cyl)')) + geom_bar()) +print(ggplot(mtcars, aes(x='mpg', y='wt', group='newcol')) + geom_line()) df = pd.DataFrame({"x": range(100), "y": range(100) }) df['newcol'] = ["steelblue" if i<25 else "coral" for i in range(len(df))] -print ggplot(df, aes(x='x', y='y', group='newcol')) + geom_line() +print(ggplot(df, aes(x='x', y='y', group='newcol')) + geom_line()) diff --git a/tests/test_aes_in_geom.py b/tests/test_aes_in_geom.py index a46e941e..257571d3 100644 --- a/tests/test_aes_in_geom.py +++ b/tests/test_aes_in_geom.py @@ -1,4 +1,4 @@ +from __future__ import print_function from ggplot import * - -print ggplot(mtcars, aes(x='wt', y='mpg')) + geom_point(aes(size='cyl'), color='blue') +print(ggplot(mtcars, aes(x='wt', y='mpg')) + geom_point(aes(size='cyl'), color='blue')) diff --git a/tests/test_area.py b/tests/test_area.py index fe3580f2..b435addc 100644 --- a/tests/test_area.py +++ b/tests/test_area.py @@ -1,7 +1,7 @@ +from __future__ import print_function from ggplot import * import pandas as pd df = pd.melt(meat[['date', 'beef', 'veal', 'pork']], id_vars=['date']).dropna() -df = pd.melt(meat[['date', 'beef', 'veal', 'pork']], id_vars=['date']).dropna() -print ggplot(df, aes(x='date', y='value', fill='variable')) + geom_area() +print(ggplot(df, aes(x='date', y='value', fill='variable')) + geom_area()) diff --git a/tests/test_art.py b/tests/test_art.py index 4a9a126b..29649b38 100644 --- a/tests/test_art.py +++ b/tests/test_art.py @@ -1,4 +1,4 @@ +from __future__ import print_function from ggplot import * - -print ggplot(diamonds, aes('price')) + geom_now_its_art() +print(ggplot(diamonds, aes('price')) + geom_now_its_art()) diff --git a/tests/test_bar.py b/tests/test_bar.py index dda512d5..87e2b01a 100644 --- a/tests/test_bar.py +++ b/tests/test_bar.py @@ -1,3 +1,4 @@ +from __future__ import print_function from ggplot import * import pandas as pd import numpy as np @@ -11,56 +12,56 @@ }) p = ggplot(mtcars, aes(x='factor(cyl)', fill='factor(gear)')) + geom_bar(position='stack') + facet_wrap('vs') -print p + scale_fill_yhat() +print(p + scale_fill_yhat()) p = ggplot(df, aes(x='x', weight='wt')) + geom_bar(color='teal') + scale_fill_identity() -print p +print(p) p = ggplot(df, aes(x='x', weight='wt', fill='filler')) + geom_bar() + scale_fill_identity() -print p +print(p) p = ggplot(df, aes(x='x', weight='wt', fill='filler')) + geom_bar(position='fill') + scale_fill_identity() -print p +print(p) # mtcars.cyl = mtcars.cyl.astype(str) # mtcars.gear = mtcars.gear.astype(str) p = ggplot(mtcars, aes(x='factor(cyl)', fill='factor(gear)')) + geom_bar(position='stack') + facet_wrap('vs') -print p +print(p) p = ggplot(mtcars, aes(x='factor(cyl)', fill='factor(gear)')) + geom_bar(position='stack') + facet_wrap('vs', 'am') -print p +print(p) # p = ggplot(mtcars, aes(x='factor(cyl)', fill='factor(gear)')) + geom_bar(position='fill') -# print p +# print(p) # # p = ggplot(df, aes(x='x', fill='filler')) + geom_bar(position='fill') + scale_fill_identity() + facet_wrap('thingy') -# print p +# print(p) # p = ggplot(df, aes(x='x', fill='filler')) + geom_bar(position='fill') + facet_wrap('thingy') -# print p +# print(p) # p = ggplot(mtcars, aes(x='factor(cyl)', fill='factor(gear)')) + geom_bar(position='fill') -# print p +# print(p) # # p = ggplot(mtcars, aes(x='factor(cyl)', fill='factor(vs)')) + geom_bar(position='fill') -# print p +# print(p) # p = ggplot(df, aes(x='x', weight='wt', fill='filler')) + geom_bar() + scale_fill_identity() -# print p +# print(p) # # p = ggplot(df, aes(x='x', fill='filler')) + geom_bar() + scale_fill_identity() -# print p +# print(p) # p = ggplot(df, aes(x='x', weight='wt')) + geom_bar() -# print p +# print(p) # # p = ggplot(df, aes(x='x')) + geom_bar() -# print p +# print(p) # p = ggplot(diamonds, aes(x='clarity', fill='cut')) + geom_bar() -# print p +# print(p) # # p = ggplot(diamonds, aes(x='clarity', fill='cut')) + geom_bar(position='fill') + facet_wrap('cut') -# print p +# print(p) diff --git a/tests/test_boxplot.py b/tests/test_boxplot.py index 44448a8b..c8d64b98 100644 --- a/tests/test_boxplot.py +++ b/tests/test_boxplot.py @@ -1,11 +1,12 @@ +from __future__ import print_function from ggplot import * import pandas as pd -print ggplot(mpg, aes(x='class', y='hwy')) + geom_boxplot() -print ggplot(mpg, aes(x='class', y='hwy')) + geom_boxplot() + facet_wrap('manufacturer') -print ggplot(diamonds, aes('pd.cut(carat, bins=10, labels=range(10))', 'price')) + geom_boxplot() +print(ggplot(mpg, aes(x='class', y='hwy')) + geom_boxplot()) +print(ggplot(mpg, aes(x='class', y='hwy')) + geom_boxplot() + facet_wrap('manufacturer')) +print(ggplot(diamonds, aes('pd.cut(carat, bins=10, labels=range(10))', 'price')) + geom_boxplot()) diamonds['clarity'] = pd.Categorical(diamonds['clarity'], ordered=True, categories='I1 SI2 SI1 VS2 VS1 VVS2 VVS1 IF'.split()) -print ggplot(diamonds, aes(x='clarity', y='price')) + geom_boxplot() +print(ggplot(diamonds, aes(x='clarity', y='price')) + geom_boxplot()) diff --git a/tests/test_element_text.py b/tests/test_element_text.py index da7e502e..bb918b9a 100644 --- a/tests/test_element_text.py +++ b/tests/test_element_text.py @@ -1,3 +1,4 @@ +from __future__ import print_function from ggplot import * # txt = element_text( @@ -23,8 +24,8 @@ # print ggplot(mtcars, aes(x='mpg')) + geom_histogram() + theme() # print ggplot(mtcars, aes(x='mpg')) + geom_histogram() + theme(plot_margin=dict(bottom=0.2, left=0.2)) # print ggplot(mtcars, aes(x='mpg')) + geom_histogram() + theme(axis_title_x=element_text(size=20, hjust=0.1, vjust=0)) -print ggplot(mtcars, aes(x='mpg')) + geom_histogram() + theme(x_axis_text=element_text(color="orange"), y_axis_text=element_text(color="blue")) -print ggplot(mtcars, aes(x='mpg')) + geom_histogram() + theme(axis_text=element_text(size=20), x_axis_text=element_text(color="orange"), y_axis_text=element_text(color="blue")) +print(ggplot(mtcars, aes(x='mpg')) + geom_histogram() + theme(x_axis_text=element_text(color="orange"), y_axis_text=element_text(color="blue"))) +print(ggplot(mtcars, aes(x='mpg')) + geom_histogram() + theme(axis_text=element_text(size=20), x_axis_text=element_text(color="orange"), y_axis_text=element_text(color="blue"))) # print ggplot(mtcars, aes(x='mpg')) + geom_histogram() + theme(plot_title=txt, axis_title_x=newTxt, axis_title_y=myY) # print ggplot(mtcars, aes(x='mpg')) + geom_histogram() + theme(title=txt, xlab=newTxt, ylab=myY) # print ggplot(mtcars, aes(x='mpg')) + geom_histogram() + facet_wrap("cyl") + theme(title=txt, xlab=newTxt, ylab=myY) diff --git a/tests/test_error_messages.py b/tests/test_error_messages.py index efc05d7c..71c67cd1 100644 --- a/tests/test_error_messages.py +++ b/tests/test_error_messages.py @@ -1,3 +1,4 @@ +from __future__ import print_function from ggplot import * -print ggplot(diamonds, aes(x='pricee')) + geom_histogram() +print(ggplot(diamonds, aes(x='pricee')) + geom_histogram()) diff --git a/tests/test_facet_scales.py b/tests/test_facet_scales.py index fb94ff0e..02fffa7d 100644 --- a/tests/test_facet_scales.py +++ b/tests/test_facet_scales.py @@ -1,20 +1,20 @@ +from __future__ import print_function from ggplot import * - p = ggplot(diamonds.sample(1000), aes(x='carat', y='price')) + geom_point() + facet_grid('cut', scales='free') -print p +print(p) p = ggplot(diamonds.sample(1000), aes(x='carat', y='price')) + geom_point() + facet_grid('cut', scales='free_x') -print p +print(p) p = ggplot(diamonds.sample(1000), aes(x='carat', y='price')) + geom_point() + facet_grid('cut', scales='free_y') -print p +print(p) p = ggplot(diamonds.sample(1000), aes(x='carat', y='price')) + geom_point() + facet_wrap('cut', scales='free') -print p +print(p) p = ggplot(diamonds.sample(1000), aes(x='carat', y='price')) + geom_point() + facet_wrap('cut', scales='free_x') -print p +print(p) p = ggplot(diamonds.sample(1000), aes(x='carat', y='price')) + geom_point() + facet_wrap('cut', scales='free_y') -print p +print(p) diff --git a/tests/test_facets.py b/tests/test_facets.py index 91443367..c5ff5e0e 100644 --- a/tests/test_facets.py +++ b/tests/test_facets.py @@ -1,3 +1,4 @@ +from __future__ import print_function import pandas as pd from ggplot import * @@ -10,9 +11,9 @@ diab = diaa.groupby(['cut','color']).quantile([x/100.0 for x in range(0,100,5)]) diab.reset_index(inplace=True) diab.columns = ['cut','color','p','stats'] -print ggplot(diab,aes(x='p', weight='stats')) + geom_bar() + facet_grid('color','cut') +print(ggplot(diab,aes(x='p', weight='stats')) + geom_bar() + facet_grid('color','cut')) -print ggplot(diamonds, aes(x='clarity', weight='price')) + geom_bar() + facet_grid('color', 'cut') -print ggplot(diamonds, aes(x='clarity', weight='price', fill='color')) + geom_bar() + facet_grid('color', 'cut') +print(ggplot(diamonds, aes(x='clarity', weight='price')) + geom_bar() + facet_grid('color', 'cut')) +print(ggplot(diamonds, aes(x='clarity', weight='price', fill='color')) + geom_bar() + facet_grid('color', 'cut')) -print ggplot(diamonds, aes(x='clarity', y='price')) + geom_boxplot() + facet_wrap('cut') +print(ggplot(diamonds, aes(x='clarity', y='price')) + geom_boxplot() + facet_wrap('cut')) diff --git a/tests/test_geom_errorbar.py b/tests/test_geom_errorbar.py index 2bf58b70..b151d780 100644 --- a/tests/test_geom_errorbar.py +++ b/tests/test_geom_errorbar.py @@ -1,4 +1,4 @@ +from __future__ import print_function from ggplot import * - -print ggplot(mpg, aes(x='class', y='hwy')) + geom_errorbar() +print(ggplot(mpg, aes(x='class', y='hwy')) + geom_errorbar()) diff --git a/tests/test_geom_histogram.py b/tests/test_geom_histogram.py index 0ed84e0f..4e38a6a1 100644 --- a/tests/test_geom_histogram.py +++ b/tests/test_geom_histogram.py @@ -1,5 +1,5 @@ +from __future__ import print_function from ggplot import * - -print ggplot(diamonds, aes(x='price')) + geom_histogram() -print ggplot(diamonds, aes(x='price')) + geom_histogram(bins=50) +print(ggplot(diamonds, aes(x='price')) + geom_histogram()) +print(ggplot(diamonds, aes(x='price')) + geom_histogram(bins=50)) diff --git a/tests/test_geom_polygon.py b/tests/test_geom_polygon.py index 6d4c3e73..6867614c 100644 --- a/tests/test_geom_polygon.py +++ b/tests/test_geom_polygon.py @@ -1,14 +1,13 @@ +from __future__ import print_function from ggplot import * import pandas as pd - - df = pd.DataFrame({ "x": [0, 1, 1, 0] + [5, 10, 10, 5], "y": [0, 0, 1, 1] + [10, 10, 20, 20], "g": ["a", "a", "a", "a"] + ["b", "b", "b", "b"] }) -print ggplot(df, aes(x='x', y='y', fill='g')) + geom_polygon() -print ggplot(df, aes(x='x', y='y', color='g')) + geom_polygon() -print ggplot(df[df.g=="b"], aes(x='x', y='y')) + geom_polygon(alpha=0.25, linetype='dashed') +print(ggplot(df, aes(x='x', y='y', fill='g')) + geom_polygon()) +print(ggplot(df, aes(x='x', y='y', color='g')) + geom_polygon()) +print(ggplot(df[df.g=="b"], aes(x='x', y='y')) + geom_polygon(alpha=0.25, linetype='dashed')) diff --git a/tests/test_index.py b/tests/test_index.py index 8291fb4a..16c80fd2 100644 --- a/tests/test_index.py +++ b/tests/test_index.py @@ -1,5 +1,6 @@ +from __future__ import print_function from ggplot import * meat = meat.set_index(['date']) -print ggplot(meat, aes(x='__index__', y='beef')) + geom_point() +print(ggplot(meat, aes(x='__index__', y='beef')) + geom_point()) diff --git a/tests/test_line.py b/tests/test_line.py index 6666d08e..8438992d 100644 --- a/tests/test_line.py +++ b/tests/test_line.py @@ -1,3 +1,4 @@ +from __future__ import print_function from ggplot import * import pandas as pd import numpy as np @@ -11,5 +12,5 @@ 'y': np.arange(100) }) -print ggplot(df, aes(x='x', y='y')) + geom_line() -print ggplot(df, aes(x='x', y='y')) + geom_path() +print(ggplot(df, aes(x='x', y='y')) + geom_line()) +print(ggplot(df, aes(x='x', y='y')) + geom_path()) diff --git a/tests/test_multiple_lines_489.py b/tests/test_multiple_lines_489.py index 9c32dd67..00d9f09a 100644 --- a/tests/test_multiple_lines_489.py +++ b/tests/test_multiple_lines_489.py @@ -1,3 +1,4 @@ +from __future__ import print_function from ggplot import * import pandas as pd @@ -5,5 +6,5 @@ df['x'] = df.index df = pd.melt(df, id_vars='x') -print df -print ggplot(aes(x='x', y='value', color='variable'), df) + geom_line() + geom_point() +print(df) +print(ggplot(aes(x='x', y='value', color='variable'), df) + geom_line() + geom_point()) diff --git a/tests/test_point.py b/tests/test_point.py index 02835df8..7341cfa4 100644 --- a/tests/test_point.py +++ b/tests/test_point.py @@ -1,7 +1,7 @@ +from __future__ import print_function from ggplot import * import pandas as pd - df = pd.melt(meat, id_vars=['date']) -print ggplot(df, aes(x='date', y='value', color='variable')) + geom_point() +print(ggplot(df, aes(x='date', y='value', color='variable')) + geom_point()) diff --git a/tests/test_rect.py b/tests/test_rect.py index 70c68c51..e19caad8 100644 --- a/tests/test_rect.py +++ b/tests/test_rect.py @@ -1,17 +1,18 @@ +from __future__ import print_function from ggplot import * import pandas as pd import numpy as np df = pd.DataFrame([{"x":2,"y":1,"z":"1","w":4},{"x":5,"y":1,"z":"1","w":2},{"x":7,"y":1,"z":"2","w":2},{"x":9,"y":1,"z":"2","w":2},{"x":12,"y":1,"z":"3","w":4},{"x":2,"y":2,"z":"3","w":4},{"x":5,"y":2,"z":"4","w":2},{"x":7,"y":2,"z":"4","w":2},{"x":9,"y":2,"z":"5","w":2},{"x":12,"y":2,"z":"5","w":4}]) -print df.head() +print(df.head()) p = ggplot(df, aes(xmin='x - w / 2', xmax='x + w / 2', ymin='y', ymax='y + 1', fill='z')) + geom_rect() -print p +print(p) p = ggplot(df, aes(xmin='x - w / 2', xmax='x + w / 2', ymin='y', ymax='y + 1', fill='z')) + geom_rect(color='black') -print p +print(p) p = ggplot(df, aes(xmin='x - w / 2', xmax='x + w / 2', ymin='y', ymax='y + 1', fill='z')) + \ geom_rect(color='black') + \ facet_wrap('w') -print p +print(p) diff --git a/tests/test_scale.py b/tests/test_scale.py index 724ed52e..1e02451f 100644 --- a/tests/test_scale.py +++ b/tests/test_scale.py @@ -1,16 +1,18 @@ +from __future__ import print_function from ggplot import * import pandas as pd + df = pd.DataFrame(dict(x=range(3), y=range(3), crayon=['sunset orange', 'inchworm', 'cadet blue'])) p = ggplot(aes(x='x', y='y', color='crayon'), data=df) p += geom_point(size=250) print(p + scale_color_crayon() + theme_bw()) p = ggplot(aes(x='x', fill='crayon'), data=df) + geom_bar() -print p + scale_fill_brewer(type='qual') +print(p + scale_fill_brewer(type='qual')) p = ggplot(aes(x='x', fill='crayon'), data=df) + geom_bar() -print p + scale_fill_crayon() +print(p + scale_fill_crayon()) p = ggplot(aes(x='x', fill='crayon'), data=df) + geom_bar() -print p + scale_fill_manual(values=['green', 'purple', 'turquoise']) +print(p + scale_fill_manual(values=['green', 'purple', 'turquoise'])) diff --git a/tests/test_stat_smooth.py b/tests/test_stat_smooth.py index da3553d3..7ca7e810 100644 --- a/tests/test_stat_smooth.py +++ b/tests/test_stat_smooth.py @@ -1,5 +1,6 @@ +from __future__ import print_function from ggplot import * -print ggplot(meat, aes(x='date', y='beef')) + stat_smooth() + scale_x_date(labels=date_format('%Y')) -print ggplot(meat, aes(x='date', y='beef')) + stat_smooth(method='ma', window=12) + scale_x_date(labels=date_format('%Y')) +print(ggplot(meat, aes(x='date', y='beef')) + stat_smooth() + scale_x_date(labels=date_format('%Y'))) +print(ggplot(meat, aes(x='date', y='beef')) + stat_smooth(method='ma', window=12) + scale_x_date(labels=date_format('%Y'))) diff --git a/tests/test_step.py b/tests/test_step.py index 836b4d6c..88bb7ddc 100644 --- a/tests/test_step.py +++ b/tests/test_step.py @@ -1,9 +1,11 @@ +from __future__ import print_function from ggplot import * import numpy as np import pandas as pd + p = ggplot(meat, aes(x='date', y='beef')) + geom_step() -print p +print(p) df = pd.DataFrame({ @@ -14,10 +16,10 @@ df.y = df.y.cumsum() p = ggplot(df, aes(x='x', y='y')) + geom_step() -print p +print(p) p = ggplot(df, aes(x='x', y='y', color='z')) + geom_step() -print p +print(p) p = ggplot(df, aes(x='x', y='y')) + geom_step() + facet_wrap("z") -print p +print(p) diff --git a/tests/test_text.py b/tests/test_text.py index d3768d31..822dad1f 100644 --- a/tests/test_text.py +++ b/tests/test_text.py @@ -1,9 +1,11 @@ +from __future__ import print_function from ggplot import * + p = ggplot(mtcars, aes(x='wt', y='mpg', label='name', color='factor(cyl)')) + geom_text() -print p -print p + geom_point() +print(p) +print(p + geom_point()) # import matplotlib.pyplot as plt # from ggplot import mtcars diff --git a/tests/test_tile.py b/tests/test_tile.py index ae347d65..988aa992 100644 --- a/tests/test_tile.py +++ b/tests/test_tile.py @@ -1,3 +1,4 @@ +from __future__ import print_function from ggplot import * import pandas as pd import numpy as np @@ -8,9 +9,9 @@ y=np.random.normal(0, 1, 1000), w=np.random.uniform(-1, 1, 1000) )) -print df.head() +print(df.head()) p = ggplot(df, aes(x='x', y='y', fill='w')) + geom_tile(interpolate=True) -print p +print(p) # p = ggplot(df, aes(x='x', y='y', fill='w')) + geom_bin2d() # print p diff --git a/tests/test_unicode.py b/tests/test_unicode.py index 0e6e275d..a6f8b677 100644 --- a/tests/test_unicode.py +++ b/tests/test_unicode.py @@ -1,5 +1,5 @@ # -*- coding: utf-8 -*- -from __future__ import unicode_literals +from __future__ import unicode_literals, print_function from ggplot import * -print ggplot(mtcars, aes(x='mpg')) + geom_histogram() + xlab("Scrüm") +print(ggplot(mtcars, aes(x='mpg')) + geom_histogram() + xlab("Scrüm")) diff --git a/tests/test_violin.py b/tests/test_violin.py index 7b66e4c7..c2fee5e4 100644 --- a/tests/test_violin.py +++ b/tests/test_violin.py @@ -1,12 +1,14 @@ +from __future__ import print_function from ggplot import * import pandas as pd + p = ggplot(mtcars, aes('factor(cyl)', 'mpg')) -print p + geom_violin() +print(p + geom_violin()) diamonds['clarity'] = pd.Categorical(diamonds['clarity'], ordered=True, categories='I1 SI2 SI1 VS2 VS1 VVS2 VVS1 IF'.split()) -print ggplot(diamonds, aes(x='clarity', y='price')) + geom_violin() +print(ggplot(diamonds, aes(x='clarity', y='price')) + geom_violin()) # import matplotlib.pyplot as plt diff --git a/tests/test_visual.py b/tests/test_visual.py index c23fdb08..a755a3e3 100644 --- a/tests/test_visual.py +++ b/tests/test_visual.py @@ -1,12 +1,12 @@ +from __future__ import print_function from ggplot import * import os -import sys import string import datetime import pandas as pd import numpy as np import random -import re + np.random.seed(10) random.seed(10) @@ -153,4 +153,4 @@ def test(description, plot): test("facet_grid with color brewer", ggplot(diamonds, aes(x='carat', y='price', shape='cut', color='clarity')) + geom_point() + scale_color_brewer() + facet_grid(x='color')) html += "\n\t\n" -print html +print(html) diff --git a/tests/tests.py b/tests/tests.py index d6a2fae0..35e46ec1 100644 --- a/tests/tests.py +++ b/tests/tests.py @@ -1,105 +1,107 @@ +from __future__ import print_function + from ggplot import * import seaborn as sns import pandas as pd import numpy as np -tips = sns.load_dataset('tips') -import sys +tips = sns.load_dataset('tips') + # p = ggplot(mtcars, aes(x='mpg', y='cyl', color='steelblue')) + geom_point() -# print p +# print(p # p = ggplot(mtcars, aes(x='mpg', y='cyl')) + geom_point(color='green') -# print p +# print(p # p = ggplot(diamonds.sample(100), aes(x='carat', y='price')) + geom_point() + facet_wrap('clarity', ncol=4) -# print p +# print(p # p = ggplot(diamonds.sample(100), aes(x='carat', y='price')) + geom_point() + facet_wrap('clarity', nrow=5) -# print p +# print(p # p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + facet_grid(x='clarity') -# print p +# print(p # p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + facet_grid(y='clarity') -# print p +# print(p # p = ggplot(diamonds.sample(1000), aes(x='carat', y='price')) + geom_point() + facet_wrap(x='clarity', y='cut') -# print p +# print(p # p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + facet_wrap(x='clarity') -# print p +# print(p # p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + facet_wrap(y='clarity') -# print p +# print(p # # p = ggplot(diamonds.sample(1000), aes(x='carat', y='price', size='clarity')) + geom_point() -# print p +# print(p # p = ggplot(diamonds.sample(1000), aes(x='carat', y='price', size='x')) + geom_point() -# print p +# print(p # p = ggplot(diamonds.sample(1000), aes(x='carat', y='price', alpha='x')) + geom_point() -# print p +# print(p # p = ggplot(diamonds.sample(1000), aes(x='carat', y='price', alpha='x')) + geom_point() + facet_grid(x='clarity') -# print p +# print(p # # p = ggplot(diamonds.sample(1000), aes(x='carat', y='price', alpha='x')) + geom_point() + facet_grid(y='clarity') -# print p +# print(p # # # shape # p = ggplot(diamonds, aes(x='carat', y='price', shape='clarity')) + geom_point() # p.save("testing.png") # # p = ggplot(diamonds.sample(100), aes(x='carat', y='price', shape='cut', color='clarity')) + geom_point() + scale_color_brewer() + facet_grid(x='color') -# print """p = ggplot(diamonds.sample(100), aes(x='carat', y='price', shape='cut', color='clarity')) + geom_point() + scale_color_brewer() + facet_grid(x='color')""", p +# print("""p = ggplot(diamonds.sample(100), aes(x='carat', y='price', shape='cut', color='clarity')) + geom_point() + scale_color_brewer() + facet_grid(x='color')""", p # # p = ggplot(diamonds.sample(100), aes(x='carat', y='price')) + geom_point() + scale_color_brewer() + facet_grid(x='color', y='clarity') -# print """p = ggplot(diamonds.sample(100), aes(x='carat', y='price')) + geom_point() + scale_color_brewer() + facet_grid(x='color', y='clarity')""", p +# print("""p = ggplot(diamonds.sample(100), aes(x='carat', y='price')) + geom_point() + scale_color_brewer() + facet_grid(x='color', y='clarity')""", p # # p = ggplot(diamonds.sample(100), aes(x='carat', y='price', shape='cut', color='clarity')) + geom_point() + scale_color_brewer() + facet_grid(y='color') -# print """p = ggplot(diamonds.sample(100), aes(x='carat', y='price', shape='cut', color='clarity')) + geom_point() + scale_color_brewer() + facet_grid(y='color')""", p +# print("""p = ggplot(diamonds.sample(100), aes(x='carat', y='price', shape='cut', color='clarity')) + geom_point() + scale_color_brewer() + facet_grid(y='color')""", p # p = ggplot(diamonds.sample(100), aes(x='carat', y='price', color='clarity')) + geom_point() + scale_color_brewer(type='div') -# print """p = ggplot(diamonds.sample(100), aes(x='carat', y='price', color='clarity')) + geom_point() + scale_color_brewer(type='div')""", p +# print("""p = ggplot(diamonds.sample(100), aes(x='carat', y='price', color='clarity')) + geom_point() + scale_color_brewer(type='div')""", p # p = ggplot(diamonds.sample(100), aes(x='carat', y='price', color='x')) + geom_point() -# print """p = ggplot(diamonds.sample(100), aes(x='carat', y='price', color='x')) + geom_point()""", p +# print("""p = ggplot(diamonds.sample(100), aes(x='carat', y='price', color='x')) + geom_point()""", p # # # # linetype # p = ggplot(diamonds.sample(100), aes(x='carat', y='price', linetype='cut')) + geom_line() -# print """p = ggplot(diamonds.sample(100), aes(x='carat', y='price', linetype='cut')) + geom_line()""", p +# print("""p = ggplot(diamonds.sample(100), aes(x='carat', y='price', linetype='cut')) + geom_line()""", p # # # # histogram # p = ggplot(diamonds, aes(x='carat')) + geom_histogram() -# print """p = ggplot(diamonds, aes(x='carat')) + geom_histogram()""", p +# print("""p = ggplot(diamonds, aes(x='carat')) + geom_histogram()""", p # # # point # p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() -# print """p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point()""", p +# print("""p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point()""", p # # # titles and stuff # p = ggplot(diamonds, aes(x='carat', y='price', color='clarity')) + geom_point() + xlab("THIS IS AN X LABEL") + ylab("THIS IS A Y LABEL") + ggtitle("THIS IS A TITLE") -# print """p = ggplot(diamonds, aes(x='carat', y='price', color='clarity')) + geom_point() + xlab("THIS IS AN X LABEL") + ylab("THIS IS A Y LABEL") + ggtitle("THIS IS A TITLE")""", p +# print("""p = ggplot(diamonds, aes(x='carat', y='price', color='clarity')) + geom_point() + xlab("THIS IS AN X LABEL") + ylab("THIS IS A Y LABEL") + ggtitle("THIS IS A TITLE")""", p # # # density # p = ggplot(diamonds, aes(x='carat')) + geom_density() -# print """p = ggplot(diamonds, aes(x='carat')) + geom_density()""", p +# print("""p = ggplot(diamonds, aes(x='carat')) + geom_density()""", p # hline p = ggplot(diamonds, aes(x='price')) + geom_hline(y=10) -print """p = ggplot(diamonds, aes(x='price')) + geom_hline(y=10)""", p +print("""p = ggplot(diamonds, aes(x='price')) + geom_hline(y=10)""", p) # vline p = ggplot(diamonds, aes(x='price')) + geom_vline(x=10) -print """p = ggplot(diamonds, aes(x='price')) + geom_vline(x=10)""", p +print("""p = ggplot(diamonds, aes(x='price')) + geom_vline(x=10)""", p) # bar p = ggplot(diamonds, aes(x='clarity')) + geom_bar() -print """p = ggplot(diamonds, aes(x='clarity')) + geom_bar()""", p +print("""p = ggplot(diamonds, aes(x='clarity')) + geom_bar()""", p) # bar w/ weight p = ggplot(diamonds, aes(x='clarity', weight='x')) + geom_bar() -print """p = ggplot(diamonds, aes(x='clarity', weight='x')) + geom_bar()""", p +print("""p = ggplot(diamonds, aes(x='clarity', weight='x')) + geom_bar()""", p) # abline p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + geom_abline(slope=5000, intercept=-500) -print """p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + geom_abline(slope=5000, intercept=-500)""", p +print("""p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + geom_abline(slope=5000, intercept=-500)""", p) # abline w/ facet p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + geom_abline(slope=5000, intercept=-500) + facet_wrap(y='clarity') -print """p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + geom_abline(slope=5000, intercept=-500) + facet_wrap(y='clarity')""", p +print("""p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + geom_abline(slope=5000, intercept=-500) + facet_wrap(y='clarity')""", p) # area df = pd.DataFrame({"x": np.arange(1000)}) @@ -107,29 +109,29 @@ df['y_high'] = df.x * 1.1 df['thing'] = ['a' if i%2==0 else 'b' for i in df.x] # p = ggplot(df, aes(x='x', ymin='y_low', ymax='y_high')) + geom_area() -# print """p = ggplot(df, aes(x='x', ymin='y_low', ymax='y_high')) + geom_area()""", p +# print("""p = ggplot(df, aes(x='x', ymin='y_low', ymax='y_high')) + geom_area()""", p # area w/ facet p = ggplot(df, aes(x='x', ymin='y_low', ymax='y_high')) + geom_area() + facet_wrap(x='thing') -print """p = ggplot(df, aes(x='x', ymin='y_low', ymax='y_high')) + geom_area() + facet_wrap(x='thing')""", p +print("""p = ggplot(df, aes(x='x', ymin='y_low', ymax='y_high')) + geom_area() + facet_wrap(x='thing')""", p) # facet wrap p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + facet_wrap(x='clarity') -print """p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + facet_wrap(x='clarity')""", p +print("""p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + facet_wrap(x='clarity')""", p) # # facet wrap w/ 2 variables p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + facet_wrap(x='color', y='cut') -print """p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + facet_wrap(x='color', y='cut')""", p +print("""p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + facet_wrap(x='color', y='cut')""", p) # facet grid w/ 1 variable p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + facet_grid(x='color') -print """p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + facet_grid(x='color')""", p +print("""p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + facet_grid(x='color')""", p) p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + facet_grid(y='color') -print """p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + facet_grid(y='color')""", p +print("""p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + facet_grid(y='color')""", p) # # facet grid w/ 2 variables p = ggplot(diamonds, aes(x='price')) + geom_histogram() + facet_grid(x='color', y='cut') -print """p = ggplot(diamonds, aes(x='price')) + geom_histogram() + facet_grid(x='color', y='cut')""", p +print("""p = ggplot(diamonds, aes(x='price')) + geom_histogram() + facet_grid(x='color', y='cut')""", p) df = pd.DataFrame({"x": np.arange(100)}) df['y'] = df.x * 10 @@ -137,145 +139,145 @@ # polar coords p = ggplot(df, aes(x='x', y='y')) + geom_point() + coord_polar() -print """p = ggplot(df, aes(x='x', y='y')) + geom_point() + coord_polar()""", p +print("""p = ggplot(df, aes(x='x', y='y')) + geom_point() + coord_polar()""", p) # equal coords p = ggplot(df, aes(x='x', y='y')) + geom_point() + coord_equal() -print """p = ggplot(df, aes(x='x', y='y')) + geom_point() + coord_equal()""", p +print("""p = ggplot(df, aes(x='x', y='y')) + geom_point() + coord_equal()""", p) # equal coords faceted p = ggplot(df, aes(x='x', y='y')) + geom_point() + coord_equal() + facet_wrap(x='z') -print """p = ggplot(df, aes(x='x', y='y')) + geom_point() + coord_equal() + facet_wrap(x='z')""", p +print("""p = ggplot(df, aes(x='x', y='y')) + geom_point() + coord_equal() + facet_wrap(x='z')""", p) # flipped coords p = ggplot(df, aes(x='x', y='y')) + geom_point() + coord_flip() -print """p = ggplot(df, aes(x='x', y='y')) + geom_point() + coord_flip()""", p +print("""p = ggplot(df, aes(x='x', y='y')) + geom_point() + coord_flip()""", p) # flipped coords facted p = ggplot(df, aes(x='x', y='y')) + geom_point() + coord_flip() + facet_grid(x='z') -print """p = ggplot(df, aes(x='x', y='y')) + geom_point() + coord_flip() + facet_grid(x='z')""", p +print("""p = ggplot(df, aes(x='x', y='y')) + geom_point() + coord_flip() + facet_grid(x='z')""", p) # x dates formatting p = ggplot(pageviews, aes(x='date_hour', y='pageviews')) + geom_line() + scale_x_date(labels=date_format('%B %-d, %Y')) -print """p = ggplot(pageviews, aes(x='date_hour', y='pageviews')) + geom_line() + scale_x_date(labels=date_format('%B %-d, %Y'))""", p +print("""p = ggplot(pageviews, aes(x='date_hour', y='pageviews')) + geom_line() + scale_x_date(labels=date_format('%B %-d, %Y'))""", p) # # x dates formatting faceted pageviews['z'] = ["a" if i%2==0 else "b" for i in range(len(pageviews))] # p = ggplot(pageviews, aes(x='date_hour', y='pageviews')) + geom_line() + scale_x_date(labels=date_format('%B %-d, %Y')) + facet_grid(y='z') -# print """p = ggplot(pageviews, aes(x='date_hour', y='pageviews')) + geom_line() + scale_x_date(labels=date_format('%B %-d, %Y')) + facet_grid(y='z')""", p +# print("""p = ggplot(pageviews, aes(x='date_hour', y='pageviews')) + geom_line() + scale_x_date(labels=date_format('%B %-d, %Y')) + facet_grid(y='z')""", p # geom_line p = ggplot(pageviews, aes(x='date_hour', y='pageviews')) + geom_line() -print """p = ggplot(pageviews, aes(x='date_hour', y='pageviews')) + geom_line()""", p +print("""p = ggplot(pageviews, aes(x='date_hour', y='pageviews')) + geom_line()""", p) # geom_line w/ facets p = ggplot(pageviews, aes(x='date_hour', y='pageviews')) + geom_line() + facet_grid(y='z') -print """p = ggplot(pageviews, aes(x='date_hour', y='pageviews')) + geom_line() + facet_grid(y='z')""", p +print("""p = ggplot(pageviews, aes(x='date_hour', y='pageviews')) + geom_line() + facet_grid(y='z')""", p) # stat_smooth w/ lm p = ggplot(tips, aes(x='total_bill', y='tip')) + stat_smooth(method='lm') -print """p = ggplot(tips, aes(x='total_bill', y='tip')) + stat_smooth(method='lm')""", p +print("""p = ggplot(tips, aes(x='total_bill', y='tip')) + stat_smooth(method='lm')""", p) # stat_smooth w/ lowess p = ggplot(tips, aes(x='total_bill', y='tip')) + stat_smooth(method='lowess') -print """p = ggplot(tips, aes(x='total_bill', y='tip')) + stat_smooth(method='lowess')""", p +print("""p = ggplot(tips, aes(x='total_bill', y='tip')) + stat_smooth(method='lowess')""", p) # stat_smooth w/ lowess and custom span p = ggplot(tips, aes(x='total_bill', y='tip')) + stat_smooth(method='lowess', span=0.2) -print """p = ggplot(tips, aes(x='total_bill', y='tip')) + stat_smooth(method='lowess', span=0.2)""", p +print("""p = ggplot(tips, aes(x='total_bill', y='tip')) + stat_smooth(method='lowess', span=0.2)""", p) # # p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + facet_wrap(x='color') -# print """p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + facet_wrap(x='color')""", p +# print("""p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + facet_wrap(x='color')""", p # # p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + facet_wrap(y='color') -# print """p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + facet_wrap(y='color')""", p +# print("""p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + facet_wrap(y='color')""", p # # p = ggplot(tips, aes(x='total_bill', y='tip', color='sex')) + geom_point() # p + scale_color_brewer(type='div') -# print """p + scale_color_brewer(type='div')""", p +# print("""p + scale_color_brewer(type='div')""", p # # p = ggplot(tips, aes(x='total_bill', y='tip', color='sex')) + geom_point() + scale_color_manual(values=['pink', 'skyblue']) -# print """p = ggplot(tips, aes(x='total_bill', y='tip', color='sex')) + geom_point() + scale_color_manual(values=['pink', 'skyblue'])""", p +# print("""p = ggplot(tips, aes(x='total_bill', y='tip', color='sex')) + geom_point() + scale_color_manual(values=['pink', 'skyblue'])""", p # # p = ggplot(tips, aes(x='total_bill', y='tip', color='tip')) + geom_point() + scale_color_gradient(low='pink', high='royalblue') -# print """p = ggplot(tips, aes(x='total_bill', y='tip', color='tip')) + geom_point() + scale_color_gradient(low='pink', high='royalblue')""", p +# print("""p = ggplot(tips, aes(x='total_bill', y='tip', color='tip')) + geom_point() + scale_color_gradient(low='pink', high='royalblue')""", p # # p = ggplot(tips, aes(x='total_bill', y='tip')) + geom_point() + scale_x_log() + scale_y_log() -# print """p = ggplot(tips, aes(x='total_bill', y='tip')) + geom_point() + scale_x_log() + scale_y_log()""", p +# print("""p = ggplot(tips, aes(x='total_bill', y='tip')) + geom_point() + scale_x_log() + scale_y_log()""", p # # p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + scale_x_log() + scale_y_log() + facet_wrap(x='color') -# print """p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + scale_x_log() + scale_y_log() + facet_wrap(x='color')""", p +# print("""p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + scale_x_log() + scale_y_log() + facet_wrap(x='color')""", p # # p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + scale_x_reverse() + scale_y_reverse() + facet_wrap(x='color') -# print """p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + scale_x_reverse() + scale_y_reverse() + facet_wrap(x='color')""", p +# print("""p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + scale_x_reverse() + scale_y_reverse() + facet_wrap(x='color')""", p # # p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + scale_x_continuous(breaks=[0, 3, 6], labels=["Low", "Medium", "High"]) + scale_y_continuous(breaks=[0, 10000, 20000], labels=["Low", "Medium", "High"]) + facet_wrap(x='color') -# print """p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + scale_x_continuous(breaks=[0, 3, 6], labels=["Low", "Medium", "High"]) + scale_y_continuous(breaks=[0, 10000, 20000], labels=["Low", "Medium", "High"]) + facet_wrap(x='color')""", p +# print("""p = ggplot(diamonds, aes(x='carat', y='price')) + geom_point() + scale_x_continuous(breaks=[0, 3, 6], labels=["Low", "Medium", "High"]) + scale_y_continuous(breaks=[0, 10000, 20000], labels=["Low", "Medium", "High"]) + facet_wrap(x='color')""", p # # p = ggplot(tips, aes(x='total_bill', y='tip', color='sex')) + geom_point() + theme_gray() -# print """p = ggplot(tips, aes(x='total_bill', y='tip', color='sex')) + geom_point() + theme_gray()""", p +# print("""p = ggplot(tips, aes(x='total_bill', y='tip', color='sex')) + geom_point() + theme_gray()""", p # # p = ggplot(tips, aes(x='total_bill', y='tip', color='sex')) + geom_point() + theme_xkcd() -# print """p = ggplot(tips, aes(x='total_bill', y='tip', color='sex')) + geom_point() + theme_xkcd()""", p +# print("""p = ggplot(tips, aes(x='total_bill', y='tip', color='sex')) + geom_point() + theme_xkcd()""", p # # p = ggplot(tips, aes(x='total_bill', y='tip', color='sex')) + geom_point() -# print """p = ggplot(tips, aes(x='total_bill', y='tip', color='sex')) + geom_point()""", p +# print("""p = ggplot(tips, aes(x='total_bill', y='tip', color='sex')) + geom_point()""", p # # p = ggplot(tips, aes(x='total_bill', y='tip')) + geom_point(color='orange') -# print """p = ggplot(tips, aes(x='total_bill', y='tip')) + geom_point(color='orange')""", p +# print("""p = ggplot(tips, aes(x='total_bill', y='tip')) + geom_point(color='orange')""", p # # p = ggplot(tips, aes(x='total_bill', y='tip', color='sex', shape='smoker', size='tip')) + geom_point() -# print """p = ggplot(tips, aes(x='total_bill', y='tip', color='sex', shape='smoker', size='tip')) + geom_point()""", p +# print("""p = ggplot(tips, aes(x='total_bill', y='tip', color='sex', shape='smoker', size='tip')) + geom_point()""", p # # p = ggplot(tips, aes(x='total_bill', y='tip', color='sex')) + geom_point() + facet_wrap(x="time") -# print """p = ggplot(tips, aes(x='total_bill', y='tip', color='sex')) + geom_point() + facet_wrap(x="time")""", p +# print("""p = ggplot(tips, aes(x='total_bill', y='tip', color='sex')) + geom_point() + facet_wrap(x="time")""", p # # p = ggplot(tips, aes(x='total_bill', y='tip', color='sex')) + geom_point() + facet_wrap(y="time") -# print """p = ggplot(tips, aes(x='total_bill', y='tip', color='sex')) + geom_point() + facet_wrap(y="time")""", p +# print("""p = ggplot(tips, aes(x='total_bill', y='tip', color='sex')) + geom_point() + facet_wrap(y="time")""", p # # p = ggplot(tips, aes(x='total_bill', y='tip', color='sex')) + geom_point() + facet_wrap(x="time") -# print """p = ggplot(tips, aes(x='total_bill', y='tip', color='sex')) + geom_point() + facet_wrap(x="time")""", p +# print("""p = ggplot(tips, aes(x='total_bill', y='tip', color='sex')) + geom_point() + facet_wrap(x="time")""", p # # p = ggplot(tips, aes(x='total_bill', y='tip', color='sex')) + geom_point() + geom_line() + facet_wrap(x="time", y="smoker") -# print """p = ggplot(tips, aes(x='total_bill', y='tip', color='sex')) + geom_point() + geom_line() + facet_wrap(x="time", y="smoker")""", p +# print("""p = ggplot(tips, aes(x='total_bill', y='tip', color='sex')) + geom_point() + geom_line() + facet_wrap(x="time", y="smoker")""", p # sys.exit(0) # # p = ggplot(tips, aes(x='total_bill', y='tip')) + geom_point() + facet_wrap(x="time", y="smoker") -# print """p = ggplot(tips, aes(x='total_bill', y='tip')) + geom_point() + facet_wrap(x="time", y="smoker")""", p +# print("""p = ggplot(tips, aes(x='total_bill', y='tip')) + geom_point() + facet_wrap(x="time", y="smoker")""", p # # p = ggplot(tips, aes(x='total_bill', y='tip')) + geom_point() + scale_color_brewer() -# print """p = ggplot(tips, aes(x='total_bill', y='tip')) + geom_point() + scale_color_brewer()""", p +# print("""p = ggplot(tips, aes(x='total_bill', y='tip')) + geom_point() + scale_color_brewer()""", p # # p = ggplot(tips, aes(x='total_bill', y='tip')) + geom_point() + theme_538() -# print """p = ggplot(tips, aes(x='total_bill', y='tip')) + geom_point() + theme_538()""", p +# print("""p = ggplot(tips, aes(x='total_bill', y='tip')) + geom_point() + theme_538()""", p # # p = ggplot(tips, aes(x='total_bill', y='tip')) + stat_smooth() + xlim(low=10, high=25) + ylim(2, 12) -# print """p = ggplot(tips, aes(x='total_bill', y='tip')) + stat_smooth() + xlim(low=10, high=25) + ylim(2, 12)""", p +# print("""p = ggplot(tips, aes(x='total_bill', y='tip')) + stat_smooth() + xlim(low=10, high=25) + ylim(2, 12)""", p # # p = ggplot(tips, aes(x='total_bill', y='tip')) + stat_smooth() + labs(x="this is x", y="this is y", title="this is title") -# print """p = ggplot(tips, aes(x='total_bill', y='tip')) + stat_smooth() + labs(x="this is x", y="this is y", title="this is title")""", p +# print("""p = ggplot(tips, aes(x='total_bill', y='tip')) + stat_smooth() + labs(x="this is x", y="this is y", title="this is title")""", p # # p = ggplot(tips, aes(x='total_bill', y='tip')) + stat_smooth() + geom_vline(x=30) + geom_hline(y=10) + ylab("GOo!") + ggtitle("This is a title") -# print """p = ggplot(tips, aes(x='total_bill', y='tip')) + stat_smooth() + geom_vline(x=30) + geom_hline(y=10) + ylab("GOo!") + ggtitle("This is a title")""", p +# print("""p = ggplot(tips, aes(x='total_bill', y='tip')) + stat_smooth() + geom_vline(x=30) + geom_hline(y=10) + ylab("GOo!") + ggtitle("This is a title")""", p # # p = ggplot(tips, aes(x='total_bill', y='tip')) + stat_smooth() + facet_wrap(x="time", y="smoker") -# print """p = ggplot(tips, aes(x='total_bill', y='tip')) + stat_smooth() + facet_wrap(x="time", y="smoker")""", p +# print("""p = ggplot(tips, aes(x='total_bill', y='tip')) + stat_smooth() + facet_wrap(x="time", y="smoker")""", p # # p = ggplot(tips, aes(x='total_bill', y='tip')) + geom_line(color="blue") + geom_point() -# print """p = ggplot(tips, aes(x='total_bill', y='tip')) + geom_line(color="blue") + geom_point()""", p +# print("""p = ggplot(tips, aes(x='total_bill', y='tip')) + geom_line(color="blue") + geom_point()""", p # # p = ggplot(tips, aes(x='total_bill', y='tip')) + geom_line(color="blue") + geom_point() + facet_wrap(x="time", y="smoker") -# print """p = ggplot(tips, aes(x='total_bill', y='tip')) + geom_line(color="blue") + geom_point() + facet_wrap(x="time", y="smoker")""", p +# print("""p = ggplot(tips, aes(x='total_bill', y='tip')) + geom_line(color="blue") + geom_point() + facet_wrap(x="time", y="smoker")""", p # # p = ggplot(tips, aes(x='total_bill')) + geom_histogram() -# print """p = ggplot(tips, aes(x='total_bill')) + geom_histogram()""", p +# print("""p = ggplot(tips, aes(x='total_bill')) + geom_histogram()""", p # # p = ggplot(tips, aes(x='total_bill')) + geom_density() -# print """p = ggplot(tips, aes(x='total_bill')) + geom_density()""", p +# print("""p = ggplot(tips, aes(x='total_bill')) + geom_density()""", p # # p = ggplot(tips, aes(x='total_bill')) + geom_density() + facet_wrap(y="time") -# print """p = ggplot(tips, aes(x='total_bill')) + geom_density() + facet_wrap(y="time")""", p +# print("""p = ggplot(tips, aes(x='total_bill')) + geom_density() + facet_wrap(y="time")""", p # tips = sns.load_dataset('tips') @@ -283,7 +285,7 @@ # # # p = geom_histogram() -# print p.layers +# print(p.layers # # g = sns.FacetGrid(tips, col="time", row="smoker") # for layer in p.layers: @@ -291,7 +293,7 @@ # plt.show() # # p = geom_density() -# print p.layers +# print(p.layers # # g = sns.FacetGrid(tips, col="time", row="smoker") # for layer in p.layers: @@ -301,7 +303,7 @@ # # # p = geom_point() + geom_line(color="blue") -# print p.layers +# print(p.layers # # g = sns.FacetGrid(tips, col="time", row="smoker") # for layer in p.layers: diff --git a/tests/tests_nan.py b/tests/tests_nan.py index f9e83706..5fba7255 100644 --- a/tests/tests_nan.py +++ b/tests/tests_nan.py @@ -1,3 +1,4 @@ +from __future__ import print_function from ggplot import * import numpy as np import pandas as pd @@ -9,10 +10,10 @@ df = pd.DataFrame(dict(x=x, y=y)) -print ggplot(df, aes(x='x', y='y')) + geom_point() -print ggplot(df, aes(x='x', y='y')) + geom_line() -print ggplot(df, aes(x='x', y='y')) + geom_step() +print(ggplot(df, aes(x='x', y='y')) + geom_point()) +print(ggplot(df, aes(x='x', y='y')) + geom_line()) +print(ggplot(df, aes(x='x', y='y')) + geom_step()) -print ggplot(df, aes(x='x')) + geom_histogram() -print ggplot(df, aes(x='x', weight='x')) + geom_histogram() -print ggplot(df, aes(x='x', weight='x')) + geom_density() +print(ggplot(df, aes(x='x')) + geom_histogram()) +print(ggplot(df, aes(x='x', weight='x')) + geom_histogram()) +print(ggplot(df, aes(x='x', weight='x')) + geom_density()) From c0ecd0a86c09cd3b7e60235bfc4561e63cc25fdb Mon Sep 17 00:00:00 2001 From: Samuel Marks <807580+SamuelMarks@users.noreply.github.com> Date: Mon, 10 Jun 2019 11:27:05 +1000 Subject: [PATCH 11/14] [*.py] Fixed spacing; [ggplot/stats/smoothers.py] Removed `from pandas.lib import Timestamp` --- docs/examples.py | 6 ++-- ggplot/aes.py | 2 +- ggplot/facets.py | 11 ++++--- ggplot/geoms/geom.py | 2 +- ggplot/geoms/geom_area.py | 2 +- ggplot/geoms/geom_bar.py | 10 +++--- ggplot/geoms/geom_boxplot.py | 12 +++---- ggplot/geoms/geom_density.py | 2 +- ggplot/geoms/geom_histogram.py | 2 +- ggplot/geoms/geom_line.py | 4 +-- ggplot/geoms/geom_step.py | 4 +-- ggplot/geoms/geom_tile.py | 2 +- ggplot/geoms/geom_violin.py | 4 +-- ggplot/ggplot.py | 47 ++++++++++++++------------- ggplot/legend.py | 12 +++---- ggplot/qplot.py | 2 +- ggplot/scales/scale_color_gradient.py | 2 +- ggplot/stats/smoothers.py | 11 +++---- ggplot/stats/stat_smooth.py | 4 +-- ggplot/themes/theme.py | 4 +-- ggplot/themes/theme_538.py | 2 +- ggplot/themes/themes.py | 7 ++-- ggplot/utils.py | 4 +-- tests/legendtest.py | 2 +- tests/test_geom_polygon.py | 2 +- tests/test_ggplot.py | 12 +++---- tests/test_visual.py | 4 +-- tests/tests.py | 6 ++-- 28 files changed, 94 insertions(+), 90 deletions(-) diff --git a/docs/examples.py b/docs/examples.py index bfbdb5fb..db123f5f 100644 --- a/docs/examples.py +++ b/docs/examples.py @@ -103,7 +103,7 @@ df = pd.DataFrame({"x": np.arange(1000)}) df['y_low'] = df.x * 0.9 df['y_high'] = df.x * 1.1 -df['thing'] = ['a' if i%2==0 else 'b' for i in df.x] +df['thing'] = ['a' if i % 2 == 0 else 'b' for i in df.x] p = ggplot(df, aes(x='x', ymin='y_low', ymax='y_high')) + geom_area() p.save("./examples/example-" + str(uuid.uuid4()) + ".png") # # area w/ facet @@ -131,7 +131,7 @@ # df = pd.DataFrame({"x": np.arange(100)}) df['y'] = df.x * 10 -df['z'] = ["a" if x%2==0 else "b" for x in df.x] +df['z'] = ["a" if x % 2 == 0 else "b" for x in df.x] # # # polar coords p = ggplot(df, aes(x='x', y='y')) + geom_point() + coord_polar() @@ -158,7 +158,7 @@ p.save("./examples/example-" + str(uuid.uuid4()) + ".png") # # # # x dates formatting faceted -pageviews['z'] = ["a" if i%2==0 else "b" for i in range(len(pageviews))] +pageviews['z'] = ["a" if i % 2 == 0 else "b" for i in range(len(pageviews))] p = ggplot(pageviews, aes(x='date_hour', y='pageviews')) + geom_line() + scale_x_date(labels=date_format('%B %-d, %Y')) + facet_grid(y='z') p.save("./examples/example-" + str(uuid.uuid4()) + ".png") # diff --git a/ggplot/aes.py b/ggplot/aes.py index f5ce220d..85c6a375 100755 --- a/ggplot/aes.py +++ b/ggplot/aes.py @@ -121,7 +121,7 @@ def _get_discrete_aes(self, df): for aes_type, column in self.data.items(): if aes_type in ['x', 'y']: continue - elif aes_type=="group": + elif aes_type == "group": discrete_aes.append((aes_type, column)) elif column not in non_numeric_columns: continue diff --git a/ggplot/facets.py b/ggplot/facets.py index be6827b9..d3b8bfb6 100644 --- a/ggplot/facets.py +++ b/ggplot/facets.py @@ -20,7 +20,7 @@ def __init__(self, data, is_wrap, rowvar=None, colvar=None, nrow=None, ncol=None # assign subplot indices to rowvars and columnvars self.ndim = ndim = self.calculate_ndimensions(data, rowvar, colvar) - if is_wrap==True: + if is_wrap: if self.nrow: self.ncol = ncol = int(math.ceil(ndim / float(self.nrow))) self.nrow = nrow = int(self.nrow) @@ -47,9 +47,9 @@ def __init__(self, data, is_wrap, rowvar=None, colvar=None, nrow=None, ncol=None value = next(facet_values) except Exception as e: continue - if ncol==1: + if ncol == 1: self.facet_map[value] = (row, None) - elif nrow==1: + elif nrow == 1: self.facet_map[value] = (None, col) else: self.facet_map[value] = (row, col) @@ -119,12 +119,13 @@ def __init__(self, x=None, y=None, nrow=None, ncol=None, scales=None): self.scales = scales def __radd__(self, gg): - if gg.__class__.__name__=="ggplot": + if gg.__class__.__name__ == "ggplot": gg.facets = Facet(gg.data, True, self.x_var, self.y_var, nrow=self.nrow, ncol=self.ncol, scales=self.scales) return gg return self + class facet_grid(object): """ Layout panels from x and (optionally) y variables in a grid format. @@ -155,7 +156,7 @@ def __init__(self, x=None, y=None, scales=None): self.scales = scales def __radd__(self, gg): - if gg.__class__.__name__=="ggplot": + if gg.__class__.__name__ == "ggplot": gg.facets = Facet(gg.data, False, self.x_var, self.y_var, scales=self.scales) return gg return self diff --git a/ggplot/geoms/geom.py b/ggplot/geoms/geom.py index 1b177368..9142c00b 100755 --- a/ggplot/geoms/geom.py +++ b/ggplot/geoms/geom.py @@ -59,7 +59,7 @@ def _get_plot_args(self, data, _aes): for key, value in _aes.items(): if value not in data: mpl_params[key] = value - elif data[value].nunique()==1: + elif data[value].nunique() == 1: mpl_params[key] = data[value].iloc[0] else: mpl_params[key] = data[value] diff --git a/ggplot/geoms/geom_area.py b/ggplot/geoms/geom_area.py index c89b3135..971e9564 100755 --- a/ggplot/geoms/geom_area.py +++ b/ggplot/geoms/geom_area.py @@ -43,7 +43,7 @@ def plot(self, ax, data, _aes): if self.last_y is None: self.last_y = pd.Series(np.repeat(0, len(data))) ymin = self.last_y - if self.DEFAULT_PARAMS['position']=="stack": + if self.DEFAULT_PARAMS['position'] == "stack": ymax = self.last_y.reset_index(drop=True) + data[variables['y']].reset_index(drop=True) else: ymax = data[variables['y']] diff --git a/ggplot/geoms/geom_bar.py b/ggplot/geoms/geom_bar.py index 1be8224b..037bb10a 100755 --- a/ggplot/geoms/geom_bar.py +++ b/ggplot/geoms/geom_bar.py @@ -91,9 +91,9 @@ def plot(self, ax, data, _aes, x_levels, fill_levels, lookups): xticks = [] for i, x_level in enumerate(x_levels): - mask = data[variables['x']]==x_level + mask = data[variables['x']] == x_level row = data[mask] - if len(row)==0: + if len(row) == 0: xticks.append(i) continue @@ -111,9 +111,9 @@ def plot(self, ax, data, _aes, x_levels, fill_levels, lookups): height = 1.0 ypos = 0 else: - mask = (lookups[variables['x']]==x_level) & (lookups[variables['fill']] == fillval) + mask = (lookups[variables['x']] == x_level) & (lookups[variables['fill']] == fillval) height = lookups[mask]['__calc_weight__'].sum() - mask = (lookups[variables['x']]==x_level) & (lookups[variables['fill']] < fillval) + mask = (lookups[variables['x']] == x_level) & (lookups[variables['fill']] < fillval) ypos = lookups[mask]['__calc_weight__'].sum() else: if fill_levels is not None: @@ -123,7 +123,7 @@ def plot(self, ax, data, _aes, x_levels, fill_levels, lookups): ypos = 0.0 height = row[weight_col].sum() - xy = (dodge + i - fill_x_adjustment, ypos) + xy = (dodge + i - fill_x_adjustment, ypos) ax.add_patch(patches.Rectangle(xy, width, height, **params)) if fill_levels is not None: diff --git a/ggplot/geoms/geom_boxplot.py b/ggplot/geoms/geom_boxplot.py index 9c6b6ee8..7550b9e5 100755 --- a/ggplot/geoms/geom_boxplot.py +++ b/ggplot/geoms/geom_boxplot.py @@ -34,7 +34,7 @@ def plot(self, ax, data, _aes, x_levels): xticks = [] for (i, xvalue) in enumerate(x_levels): - subset = data[data[variables['x']]==xvalue] + subset = data[data[variables['x']] == xvalue] xi = np.repeat(i, len(subset)) yvalues = subset[variables['y']] xticks.append(i) @@ -42,22 +42,22 @@ def plot(self, ax, data, _aes, x_levels): bounds_25_75 = yvalues.quantile([0.25, 0.75]).values bounds_5_95 = yvalues.quantile([0.05, 0.95]).values - if self.params.get('outliers', True)==True: + if self.params.get('outliers', True): mask = ((yvalues > bounds_5_95[1]) | (yvalues < bounds_5_95[0])).values ax.scatter(x=xi[mask], y=yvalues[mask], c=self.params.get('outlier_color', 'black')) - if self.params.get('lines', True)==True: + if self.params.get('lines', True): ax.vlines(x=i, ymin=bounds_25_75[1], ymax=bounds_5_95[1]) ax.vlines(x=i, ymin=bounds_5_95[0], ymax=bounds_25_75[0]) - if self.params.get('notch', False)==True: + if self.params.get('notch', False): ax.hlines(bounds_5_95[0], i - 0.25/2, i + 0.25/2, linewidth=2) ax.hlines(bounds_5_95[1], i - 0.25/2, i + 0.25/2, linewidth=2) - if self.params.get('median', True)==True: + if self.params.get('median', True): ax.hlines(yvalues.median(), i - 0.25, i + 0.25, linewidth=2) - if self.params.get('box', True)==True: + if self.params.get('box', True): params = { 'facecolor': 'white', 'edgecolor': 'black', diff --git a/ggplot/geoms/geom_density.py b/ggplot/geoms/geom_density.py index b306f587..e31f0959 100755 --- a/ggplot/geoms/geom_density.py +++ b/ggplot/geoms/geom_density.py @@ -49,6 +49,6 @@ def plot(self, ax, data, _aes): params = self._get_plot_args(data, _aes) variables = _aes.data x = data[variables['x']] - x = x[x.isnull()==False] + x = x[x.isnull() is False] x, y = self._calculate_density(x) ax.plot(x, y, **params) diff --git a/ggplot/geoms/geom_histogram.py b/ggplot/geoms/geom_histogram.py index 9940b857..22d1078e 100755 --- a/ggplot/geoms/geom_histogram.py +++ b/ggplot/geoms/geom_histogram.py @@ -42,7 +42,7 @@ def plot(self, ax, data, _aes): variables = _aes.data x = data[variables['x']] - x = x[x.isnull()==False] + x = x[x.isnull() is False] if 'binwidth' in self.params: params['bins'] = np.arange(np.min(x), np.max(x) + self.params['binwidth'], self.params['binwidth']) diff --git a/ggplot/geoms/geom_line.py b/ggplot/geoms/geom_line.py index c6dc72a6..006aae30 100755 --- a/ggplot/geoms/geom_line.py +++ b/ggplot/geoms/geom_line.py @@ -37,8 +37,8 @@ def plot(self, ax, data, _aes): y = data[variables['y']] nulls = (x.isnull() | y.isnull()) - x = x[nulls==False] - y = y[nulls==False] + x = x[nulls is False] + y = y[nulls is False] if self.is_path: pass diff --git a/ggplot/geoms/geom_step.py b/ggplot/geoms/geom_step.py index 2d46c7bb..efc0f0c3 100755 --- a/ggplot/geoms/geom_step.py +++ b/ggplot/geoms/geom_step.py @@ -37,8 +37,8 @@ def plot(self, ax, data, _aes): y = data[variables['y']] nulls = (x.isnull() | y.isnull()) - x = x[nulls==False] - y = y[nulls==False] + x = x[nulls is False] + y = y[nulls is False] xs = [None] * (2 * (len(x)-1)) ys = [None] * (2 * (len(x)-1)) diff --git a/ggplot/geoms/geom_tile.py b/ggplot/geoms/geom_tile.py index 17e44d48..efed3ed8 100755 --- a/ggplot/geoms/geom_tile.py +++ b/ggplot/geoms/geom_tile.py @@ -55,7 +55,7 @@ def plot(self, ax, data, _aes): counts = data[[weight, variables['x'] + "_cut", variables['y'] + "_cut"]].groupby([variables['x'] + "_cut", variables['y'] + "_cut"]).count().fillna(0) weighted = data[[weight, variables['x'] + "_cut", variables['y'] + "_cut"]].groupby([variables['x'] + "_cut", variables['y'] + "_cut"]).sum().fillna(0) - if self.params['interpolate']==False: + if self.params['interpolate'] is False: def get_xy(): for x in x_bins: for y in y_bins: diff --git a/ggplot/geoms/geom_violin.py b/ggplot/geoms/geom_violin.py index f4c69b07..6fec6064 100755 --- a/ggplot/geoms/geom_violin.py +++ b/ggplot/geoms/geom_violin.py @@ -27,8 +27,8 @@ def plot(self, ax, data, _aes, x_levels): variables = _aes.data xticks = [] - for (i, xvalue) in enumerate(x_levels): - subset = data[data[variables['x']]==xvalue] + for i, xvalue in enumerate(x_levels): + subset = data[data[variables['x']] == xvalue] yi = subset[variables['y']].values # so this is weird, apparently violinplot is *the only plot that diff --git a/ggplot/ggplot.py b/ggplot/ggplot.py index 98707f7d..d96c2a2e 100755 --- a/ggplot/ggplot.py +++ b/ggplot/ggplot.py @@ -23,6 +23,7 @@ if os.environ.get("GGPLOT_DEV"): from PIL import Image + class ggplot(object): """ ggplot is the base layer or object that you use to define @@ -192,13 +193,13 @@ def apply_theme(self): warnings.warn(msg, RuntimeWarning) def apply_coords(self): - if self.coords=="equal": + if self.coords == "equal": for ax in self._iterate_subplots(): min_val = np.min([np.min(ax.get_yticks()), np.min(ax.get_xticks())]) max_val = np.max([np.max(ax.get_yticks()), np.max(ax.get_xticks())]) ax.set_xticks(np.linspace(min_val, max_val, 7)) ax.set_yticks(np.linspace(min_val, max_val, 7)) - elif self.coords=="flip": + elif self.coords == "flip": if 'x' in self._aes.data and 'y' in self._aes.data: x = self._aes.data['x'] y = self._aes.data['y'] @@ -337,17 +338,17 @@ def _get_mapping(self, aes_type, colname): from "a" => "#4682B4". """ mapping = None - if aes_type=="color": + if aes_type == "color": mapping = discretemappers.color_gen(self.data[colname].nunique(), colors=self.manual_color_list) - elif aes_type=="fill": + elif aes_type == "fill": mapping = discretemappers.color_gen(self.data[colname].nunique(), colors=self.manual_fill_list) - elif aes_type=="shape": + elif aes_type == "shape": mapping = discretemappers.shape_gen() - elif aes_type=="linetype": + elif aes_type == "linetype": mapping = discretemappers.linetype_gen() - elif aes_type=="size": + elif aes_type == "size": mapping = discretemappers.size_gen(self.data[colname].unique()) - elif aes_type=="group": + elif aes_type == "group": mapping = discretemappers.identity_gen(self.data[colname].unique()) return mapping @@ -425,11 +426,11 @@ def make_facets(self): "Creates figure and axes for m x n facet grid/wrap" sharex, sharey = True, True if self.facets: - if self.facets.scales=="free": + if self.facets.scales == "free": sharex, sharey = False, False - elif self.facets.scales=="free_x": + elif self.facets.scales == "free_x": sharex, sharey = False, True - elif self.facets.scales=="free_y": + elif self.facets.scales == "free_y": sharex, sharey = True, False facet_params = dict(sharex=sharex, sharey=sharey) @@ -438,7 +439,7 @@ def make_facets(self): facet_params['nrows'] = nrow facet_params['ncols'] = ncol - if self.coords=="polar": + if self.coords == "polar": facet_params['subplot_kw'] = { "polar": True } fig, axs = plt.subplots(**facet_params) @@ -463,7 +464,8 @@ def get_facet_groups(self, group): col_variable = self.facets.colvar row_variable = self.facets.rowvar - if self.facets.is_wrap==True: + font = {'fontsize': 10} + if self.facets.is_wrap: groups = [row_variable, col_variable] groups = [g for g in groups if g] for (i, (name, subgroup)) in enumerate(group.groupby(groups)): @@ -472,12 +474,11 @@ def get_facet_groups(self, group): # this only happens when a field is being used both as a facet parameter AND as a discrete aesthetic (i.e. shape) row, col = self.facets.facet_map[name] - if len(self.subplots.shape)==1: + if len(self.subplots.shape) == 1: ax = self.subplots[i] else: ax = self.get_subplot(row, col) - font = { 'fontsize': 10 } yield (ax, subgroup) for item in self.facets.generate_subplot_index(self.data, self.facets.rowvar, self.facets.colvar): @@ -510,7 +511,7 @@ def get_facet_groups(self, group): for (_, (colname, subgroup)) in enumerate(group.groupby(col_variable)): row, col = self.facets.facet_map[colname] ax = self.subplots[col] - if self.facets.is_wrap==True: + if self.facets.is_wrap: ax.set_title("%s=%s" % (col_variable, colname)) else: ax.set_title(colname, fontdict={'fontsize': 10}) @@ -520,7 +521,7 @@ def get_facet_groups(self, group): for (row, (rowname, subgroup)) in enumerate(group.groupby(row_variable)): row, col = self.facets.facet_map[rowname] - if self.facets.is_wrap==True: + if self.facets.is_wrap: ax = self.subplots[row] ax.set_title("%s=%s" % (row_variable, rowname)) else: @@ -585,7 +586,7 @@ def _prep_layer_for_plotting(self, layer, facetgroup): function on them. This function performs those perperations and then returns a dictionary of **kwargs for the layer.plot function to use. """ - if layer.__class__.__name__=="geom_bar": + if layer.__class__.__name__ == "geom_bar": mask = True df = layer.setup_data(self.data, self._aes, facets=self.facets) if df is None: @@ -593,7 +594,7 @@ def _prep_layer_for_plotting(self, layer, facetgroup): if self.facets: facet_filter = facetgroup[self.facets.facet_cols].iloc[0].to_dict() for k, v in facet_filter.items(): - mask = (mask) & (df[k]==v) + mask = mask & (df[k] == v) df = df[mask] if 'fill' in self._aes: @@ -610,7 +611,7 @@ def _prep_layer_for_plotting(self, layer, facetgroup): return dict() def make(self): - "Constructs the plot using the methods. This is the 'main' for ggplot" + """Constructs the plot using the methods. This is the 'main' for ggplot""" plt.close() with mpl.rc_context(): self.apply_theme() @@ -619,8 +620,8 @@ def make(self): self.fig, self.subplots = self.make_facets() else: subplot_kw = {} - if self.coords=="polar": - subplot_kw = { "polar": True } + if self.coords == "polar": + subplot_kw = {"polar": True} self.fig, self.subplots = plt.subplots(subplot_kw=subplot_kw) self.apply_scales() @@ -631,7 +632,7 @@ def make(self): for ax, facetgroup in self.get_facet_groups(group): for layer in self.layers: kwargs = self._prep_layer_for_plotting(layer, facetgroup) - if kwargs==False: + if kwargs is False: continue layer.plot(ax, facetgroup, self._aes, **kwargs) diff --git a/ggplot/legend.py b/ggplot/legend.py index ca894cf8..c29f6694 100644 --- a/ggplot/legend.py +++ b/ggplot/legend.py @@ -44,17 +44,17 @@ def linetype_legend(linetype): return plt.Line2D([0],[0], color='black', linestyle=linetype) def make_aesthetic_legend(aesthetic, value): - if aesthetic=='color': + if aesthetic == 'color': return color_legend(value) - elif aesthetic=='fill': + elif aesthetic == 'fill': return color_legend(value) - elif aesthetic=='size': + elif aesthetic == 'size': return size_legend(value) - elif aesthetic=='alpha': + elif aesthetic == 'alpha': return alpha_legend(value) - elif aesthetic=='shape': + elif aesthetic == 'shape': return shape_legend(value) - elif aesthetic=='linetype': + elif aesthetic == 'linetype': return linetype_legend(value) else: print(aesthetic + " not found") diff --git a/ggplot/qplot.py b/ggplot/qplot.py index 9ef231d6..19222be5 100644 --- a/ggplot/qplot.py +++ b/ggplot/qplot.py @@ -101,7 +101,7 @@ def qplot(x, y=None, color=None, size=None, fill=None, data=None, "point": geom_point, } # taking our best guess - if geom=="auto": + if geom == "auto": if y is None: geom = geom_histogram else: diff --git a/ggplot/scales/scale_color_gradient.py b/ggplot/scales/scale_color_gradient.py index 9fa96500..e47083d6 100644 --- a/ggplot/scales/scale_color_gradient.py +++ b/ggplot/scales/scale_color_gradient.py @@ -30,7 +30,7 @@ class scale_color_gradient(scale): Examples -------- >>> from ggplot import * - >>> diamons_premium = diamonds[diamonds.cut=='Premium'] + >>> diamons_premium = diamonds[diamonds.cut == 'Premium'] >>> gg = ggplot(diamons_premium, aes(x='depth', y='carat', colour='price')) + \\ ... geom_point() >>> print(gg + scale_colour_gradient(low='red', mid='white', high='blue', limits=[4000,6000]) + \\ diff --git a/ggplot/stats/smoothers.py b/ggplot/stats/smoothers.py index cb18135a..8aa1d077 100644 --- a/ggplot/stats/smoothers.py +++ b/ggplot/stats/smoothers.py @@ -1,7 +1,6 @@ from __future__ import (absolute_import, division, print_function, unicode_literals) import numpy as np -from pandas.lib import Timestamp import pandas as pd import statsmodels.api as sm from statsmodels.nonparametric.smoothers_lowess import lowess as smlowess @@ -19,8 +18,8 @@ datetime.time ) _isdate = lambda x: isinstance(x, date_types) -SPAN = 2/3. -ALPHA = 0.05 # significance level for confidence interval +SPAN = 2 / 3. +ALPHA = 0.05 # significance level for confidence interval def _snakify(txt): txt = txt.strip().lower() @@ -49,7 +48,7 @@ def lm(x, y, alpha=ALPHA): predict_ci_upp = df['predict_ci_95%_upp'].values if x_is_date: - x = [Timestamp.fromordinal(int(i)) for i in x] + x = [pd.Timestamp.fromordinal(int(i)) for i in x] return (x, fittedvalues, predict_mean_ci_low, predict_mean_ci_upp) def lowess(x, y, span=SPAN): @@ -71,7 +70,7 @@ def lowess(x, y, span=SPAN): y2 = pd.Series(upper * std + y) if x_is_date: - x = [Timestamp.fromordinal(int(i)) for i in x] + x = [pd.Timestamp.fromordinal(int(i)) for i in x] return (x, y, y1, y2) @@ -87,5 +86,5 @@ def mavg(x,y, window): y2 = y + std_err if x_is_date: - x = [Timestamp.fromordinal(int(i)) for i in x] + x = [pd.Timestamp.fromordinal(int(i)) for i in x] return (x, y, y1, y2) diff --git a/ggplot/stats/stat_smooth.py b/ggplot/stats/stat_smooth.py index 2264a6aa..ea5a3925 100644 --- a/ggplot/stats/stat_smooth.py +++ b/ggplot/stats/stat_smooth.py @@ -86,7 +86,7 @@ def plot(self, ax, data, _aes): params['alpha'] = 0.2 order = np.argsort(x) - if self.params.get('se', True)==True: + if self.params.get('se', True): if is_date(smoothed_data.x.iloc[0]): dtype = smoothed_data.x.iloc[0].__class__ x = np.array([i.toordinal() for i in smoothed_data.x]) @@ -95,6 +95,6 @@ def plot(self, ax, data, _aes): ax.set_xticklabels(new_ticks) else: ax.fill_between(smoothed_data.x, smoothed_data.y1, smoothed_data.y2, **params) - if self.params.get('fit', True)==True: + if self.params.get('fit', True): del params['alpha'] ax.plot(smoothed_data.x, smoothed_data.y, **params) diff --git a/ggplot/themes/theme.py b/ggplot/themes/theme.py index 1bccf16a..c4b0e70a 100644 --- a/ggplot/themes/theme.py +++ b/ggplot/themes/theme.py @@ -50,7 +50,7 @@ def __init__(self): pass def __radd__(self, other): - if other.__class__.__name__=="ggplot": + if other.__class__.__name__ == "ggplot": other.theme = self return other @@ -124,7 +124,7 @@ def __init__(self, *args, **kwargs): self.things = deepcopy(kwargs) def __radd__(self, other): - if other.__class__.__name__=="ggplot": + if other.__class__.__name__ == "ggplot": other.theme = self for key, value in self.things.items(): try: diff --git a/ggplot/themes/theme_538.py b/ggplot/themes/theme_538.py index d9182f25..06790ab0 100644 --- a/ggplot/themes/theme_538.py +++ b/ggplot/themes/theme_538.py @@ -1,9 +1,9 @@ from __future__ import (absolute_import, division, print_function, unicode_literals) -from cycler import cycler from .theme import theme_base from cycler import cycler + class theme_538(theme_base): """ Theme for 538. diff --git a/ggplot/themes/themes.py b/ggplot/themes/themes.py index 408d1e62..5ef6ab4b 100644 --- a/ggplot/themes/themes.py +++ b/ggplot/themes/themes.py @@ -1,15 +1,18 @@ from __future__ import (absolute_import, division, print_function, unicode_literals) + +from copy import deepcopy, copy + import matplotlib as mpl import matplotlib.pyplot as plt -from cycler import cycler + class theme(object): def __init__(self): self._rcParams = {} def __radd__(self, other): - if other.__class__.__name__=="ggplot": + if other.__class__.__name__ == "ggplot": other.theme = self return other diff --git a/ggplot/utils.py b/ggplot/utils.py index 16970273..e83de79a 100644 --- a/ggplot/utils.py +++ b/ggplot/utils.py @@ -59,8 +59,8 @@ def is_categorical(obj): - booleans """ try: - k = float(obj.iloc[0]) - return is_sequence_of_strings(k) or is_sequence_of_booleans(k) + float(obj.iloc[0]) + return is_sequence_of_strings(obj) or is_sequence_of_booleans(obj) except: return True diff --git a/tests/legendtest.py b/tests/legendtest.py index 9946baba..e0b9694a 100644 --- a/tests/legendtest.py +++ b/tests/legendtest.py @@ -7,7 +7,7 @@ from scales.scale_identity import scale_fill_identity -mtcars['newcol'] = ["steelblue" if i%2==0 else "coral" for i in range(len(mtcars))] +mtcars['newcol'] = ["steelblue" if i % 2 == 0 else "coral" for i in range(len(mtcars))] print(ggplot(mtcars, aes(x='mpg', fill='newcol')) + geom_histogram() + scale_fill_identity()) print(ggplot(mtcars, aes(x='wt', y='mpg', color='newcol', shape='newcol')) + geom_point()) print(ggplot(mtcars, aes(x='mpg', y='wt')) + geom_point(color='royalblue')) diff --git a/tests/test_geom_polygon.py b/tests/test_geom_polygon.py index 6867614c..bba3a13d 100644 --- a/tests/test_geom_polygon.py +++ b/tests/test_geom_polygon.py @@ -10,4 +10,4 @@ print(ggplot(df, aes(x='x', y='y', fill='g')) + geom_polygon()) print(ggplot(df, aes(x='x', y='y', color='g')) + geom_polygon()) -print(ggplot(df[df.g=="b"], aes(x='x', y='y')) + geom_polygon(alpha=0.25, linetype='dashed')) +print(ggplot(df[df.g == "b"], aes(x='x', y='y')) + geom_polygon(alpha=0.25, linetype='dashed')) diff --git a/tests/test_ggplot.py b/tests/test_ggplot.py index 0417d66a..b5f390a6 100644 --- a/tests/test_ggplot.py +++ b/tests/test_ggplot.py @@ -127,32 +127,32 @@ def test_scale_y_log_base(self): def test_scale_alpha_identity(self): df = pd.DataFrame({'x': range(10), 'the-alpha': '+' }) p = gg.ggplot(gg.aes(x='x', alpha='the-alpha'), df) + gg.scale_alpha_identity() - self.assertTrue((p.data['the-alpha']==df['the-alpha']).all()) + self.assertTrue((p.data['the-alpha'] == df['the-alpha']).all()) def test_scale_color_identity(self): df = pd.DataFrame({'x': range(10), 'the-color': 'blue' }) p = gg.ggplot(gg.aes(x='x', color='the-color'), df) + gg.scale_color_identity() - self.assertTrue((p.data['the-color']==df['the-color']).all()) + self.assertTrue((p.data['the-color'] == df['the-color']).all()) def test_scale_fill_identity(self): df = pd.DataFrame({'x': range(10), 'the-fill': '+' }) p = gg.ggplot(gg.aes(x='x', fill='the-fill'), df) + gg.scale_fill_identity() - self.assertTrue((p.data['the-fill']==df['the-fill']).all()) + self.assertTrue((p.data['the-fill'] == df['the-fill']).all()) def test_scale_linetype_identity(self): df = pd.DataFrame({'x': range(10), 'the-linetype': '+' }) p = gg.ggplot(gg.aes(x='x', linetype='the-linetype'), df) + gg.scale_linetype_identity() - self.assertTrue((p.data['the-linetype']==df['the-linetype']).all()) + self.assertTrue((p.data['the-linetype'] == df['the-linetype']).all()) def test_scale_shape_identity(self): df = pd.DataFrame({'x': range(10), 'the-shape': '+' }) p = gg.ggplot(gg.aes(x='x', shape='the-shape'), df) + gg.scale_shape_identity() - self.assertTrue((p.data['the-shape']==df['the-shape']).all()) + self.assertTrue((p.data['the-shape'] == df['the-shape']).all()) def test_scale_size_identity(self): df = pd.DataFrame({'x': range(10), 'the-size': '+' }) p = gg.ggplot(gg.aes(x='x', size='the-size'), df) + gg.scale_size_identity() - self.assertTrue((p.data['the-size']==df['the-size']).all()) + self.assertTrue((p.data['the-size'] == df['the-size']).all()) def test_scale_x_reverse(self): df = pd.DataFrame({'x': range(10), 'the-size': '+' }) diff --git a/tests/test_visual.py b/tests/test_visual.py index a755a3e3..4c4bb274 100644 --- a/tests/test_visual.py +++ b/tests/test_visual.py @@ -69,10 +69,10 @@ def test(description, plot): "g": ["a", "a", "a", "a"] + ["b", "b", "b", "b"] }) -test("geom_polygon basic", ggplot(df[df.g=="a"], aes(x='x', y='y')) + geom_polygon()) +test("geom_polygon basic", ggplot(df[df.g == "a"], aes(x='x', y='y')) + geom_polygon()) test("geom_polygon fill", ggplot(df, aes(x='x', y='y', fill='g')) + geom_polygon()) test("geom_polygon color", ggplot(df, aes(x='x', y='y', color='g')) + geom_polygon()) -test("geom_polygon with alpha parameter", ggplot(df[df.g=="b"], aes(x='x', y='y')) + geom_polygon(alpha=0.25)) +test("geom_polygon with alpha parameter", ggplot(df[df.g == "b"], aes(x='x', y='y')) + geom_polygon(alpha=0.25)) test("geom_polygon linetype and size parameters", ggplot(df, aes(x='x', y='y', color='g')) + geom_polygon(linetype='dashed', size=10)) # geom_errorbar diff --git a/tests/tests.py b/tests/tests.py index 35e46ec1..8a7b9b01 100644 --- a/tests/tests.py +++ b/tests/tests.py @@ -107,7 +107,7 @@ df = pd.DataFrame({"x": np.arange(1000)}) df['y_low'] = df.x * 0.9 df['y_high'] = df.x * 1.1 -df['thing'] = ['a' if i%2==0 else 'b' for i in df.x] +df['thing'] = ['a' if i % 2 == 0 else 'b' for i in df.x] # p = ggplot(df, aes(x='x', ymin='y_low', ymax='y_high')) + geom_area() # print("""p = ggplot(df, aes(x='x', ymin='y_low', ymax='y_high')) + geom_area()""", p # area w/ facet @@ -135,7 +135,7 @@ df = pd.DataFrame({"x": np.arange(100)}) df['y'] = df.x * 10 -df['z'] = ["a" if x%2==0 else "b" for x in df.x] +df['z'] = ["a" if x % 2 == 0 else "b" for x in df.x] # polar coords p = ggplot(df, aes(x='x', y='y')) + geom_point() + coord_polar() @@ -162,7 +162,7 @@ print("""p = ggplot(pageviews, aes(x='date_hour', y='pageviews')) + geom_line() + scale_x_date(labels=date_format('%B %-d, %Y'))""", p) # # x dates formatting faceted -pageviews['z'] = ["a" if i%2==0 else "b" for i in range(len(pageviews))] +pageviews['z'] = ["a" if i % 2 == 0 else "b" for i in range(len(pageviews))] # p = ggplot(pageviews, aes(x='date_hour', y='pageviews')) + geom_line() + scale_x_date(labels=date_format('%B %-d, %Y')) + facet_grid(y='z') # print("""p = ggplot(pageviews, aes(x='date_hour', y='pageviews')) + geom_line() + scale_x_date(labels=date_format('%B %-d, %Y')) + facet_grid(y='z')""", p From b07619bdcc1febfde275b6e3d4259e1255eddba0 Mon Sep 17 00:00:00 2001 From: Samuel Marks <807580+SamuelMarks@users.noreply.github.com> Date: Mon, 10 Jun 2019 12:59:58 +1000 Subject: [PATCH 12/14] [ggplot/scales/scale_color_brewer.py] Choose largest pallet if pallet chosen is > max --- ggplot/scales/scale_color_brewer.py | 12 ++++++++++-- 1 file changed, 10 insertions(+), 2 deletions(-) diff --git a/ggplot/scales/scale_color_brewer.py b/ggplot/scales/scale_color_brewer.py index d73393b1..465813bc 100644 --- a/ggplot/scales/scale_color_brewer.py +++ b/ggplot/scales/scale_color_brewer.py @@ -1,7 +1,7 @@ from __future__ import (absolute_import, division, print_function, unicode_literals) + from .scale import scale -from copy import deepcopy import brewer2mpl @@ -73,7 +73,15 @@ def __radd__(self, gg): # only one color used n_colors = 3 - bmap = brewer2mpl.get_map(palette, ctype, n_colors) + try: + bmap = brewer2mpl.get_map(palette, ctype, n_colors) + except ValueError as e: + if not str(e).startswith('Invalid number for map type'): + raise e + palettes = brewer2mpl.COLOR_MAPS[_handle_shorthand(ctype).lower().capitalize()][palette] + n_colors = int(max(str(k) for k in palettes)) + bmap = brewer2mpl.get_map(palette, ctype, n_colors) + gg.manual_color_list = bmap.hex_colors return gg From 211ccca971784a6ccaeb82d7ea81d610f8ec9c40 Mon Sep 17 00:00:00 2001 From: Samuel Marks <807580+SamuelMarks@users.noreply.github.com> Date: Mon, 10 Jun 2019 14:40:08 +1000 Subject: [PATCH 13/14] [*.py] Revert `is False` replacement of `== False` --- ggplot/geoms/geom_density.py | 2 +- ggplot/geoms/geom_histogram.py | 2 +- ggplot/geoms/geom_line.py | 4 ++-- ggplot/geoms/geom_step.py | 4 ++-- ggplot/geoms/geom_tile.py | 2 +- ggplot/ggplot.py | 2 +- 6 files changed, 8 insertions(+), 8 deletions(-) diff --git a/ggplot/geoms/geom_density.py b/ggplot/geoms/geom_density.py index e31f0959..27995920 100755 --- a/ggplot/geoms/geom_density.py +++ b/ggplot/geoms/geom_density.py @@ -49,6 +49,6 @@ def plot(self, ax, data, _aes): params = self._get_plot_args(data, _aes) variables = _aes.data x = data[variables['x']] - x = x[x.isnull() is False] + x = x[x.isnull() == False] x, y = self._calculate_density(x) ax.plot(x, y, **params) diff --git a/ggplot/geoms/geom_histogram.py b/ggplot/geoms/geom_histogram.py index 22d1078e..b54ce418 100755 --- a/ggplot/geoms/geom_histogram.py +++ b/ggplot/geoms/geom_histogram.py @@ -42,7 +42,7 @@ def plot(self, ax, data, _aes): variables = _aes.data x = data[variables['x']] - x = x[x.isnull() is False] + x = x[x.isnull() == False] if 'binwidth' in self.params: params['bins'] = np.arange(np.min(x), np.max(x) + self.params['binwidth'], self.params['binwidth']) diff --git a/ggplot/geoms/geom_line.py b/ggplot/geoms/geom_line.py index 006aae30..25488bdc 100755 --- a/ggplot/geoms/geom_line.py +++ b/ggplot/geoms/geom_line.py @@ -37,8 +37,8 @@ def plot(self, ax, data, _aes): y = data[variables['y']] nulls = (x.isnull() | y.isnull()) - x = x[nulls is False] - y = y[nulls is False] + x = x[nulls == False] + y = y[nulls == False] if self.is_path: pass diff --git a/ggplot/geoms/geom_step.py b/ggplot/geoms/geom_step.py index efc0f0c3..16957c14 100755 --- a/ggplot/geoms/geom_step.py +++ b/ggplot/geoms/geom_step.py @@ -37,8 +37,8 @@ def plot(self, ax, data, _aes): y = data[variables['y']] nulls = (x.isnull() | y.isnull()) - x = x[nulls is False] - y = y[nulls is False] + x = x[nulls == False] + y = y[nulls == False] xs = [None] * (2 * (len(x)-1)) ys = [None] * (2 * (len(x)-1)) diff --git a/ggplot/geoms/geom_tile.py b/ggplot/geoms/geom_tile.py index efed3ed8..cddc52b7 100755 --- a/ggplot/geoms/geom_tile.py +++ b/ggplot/geoms/geom_tile.py @@ -55,7 +55,7 @@ def plot(self, ax, data, _aes): counts = data[[weight, variables['x'] + "_cut", variables['y'] + "_cut"]].groupby([variables['x'] + "_cut", variables['y'] + "_cut"]).count().fillna(0) weighted = data[[weight, variables['x'] + "_cut", variables['y'] + "_cut"]].groupby([variables['x'] + "_cut", variables['y'] + "_cut"]).sum().fillna(0) - if self.params['interpolate'] is False: + if self.params['interpolate'] == False: def get_xy(): for x in x_bins: for y in y_bins: diff --git a/ggplot/ggplot.py b/ggplot/ggplot.py index d96c2a2e..09ac1725 100755 --- a/ggplot/ggplot.py +++ b/ggplot/ggplot.py @@ -632,7 +632,7 @@ def make(self): for ax, facetgroup in self.get_facet_groups(group): for layer in self.layers: kwargs = self._prep_layer_for_plotting(layer, facetgroup) - if kwargs is False: + if not kwargs: continue layer.plot(ax, facetgroup, self._aes, **kwargs) From eb9d534446f057dd2c449de76457097bce7a0fa1 Mon Sep 17 00:00:00 2001 From: Samuel Marks <807580+SamuelMarks@users.noreply.github.com> Date: Mon, 10 Jun 2019 14:49:03 +1000 Subject: [PATCH 14/14] [chart_components.py] `is not None` to replace `!= None`; [ggplot.py] `fill_levels` now set correctly for new Pandas --- ggplot/chart_components.py | 8 ++++---- ggplot/ggplot.py | 2 +- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/ggplot/chart_components.py b/ggplot/chart_components.py index 6d82f3f0..dcf248c8 100644 --- a/ggplot/chart_components.py +++ b/ggplot/chart_components.py @@ -46,13 +46,13 @@ class xlim(object): >>> ggplot(mpg, aes(x='hwy')) + geom_hisotgram() + xlim(0, 20) """ def __init__(self, low = None, high = None): - if low != None : + if low is not None: try: _ = low - 0 except TypeError: raise Exception("The 'low' argument to", self.__class__.__name__, "must be of a numeric type or None") - if high != None : + if high is not None: try: _ = high - 0 except TypeError: @@ -83,13 +83,13 @@ class ylim(object): >>> ggplot(mpg, aes(x='hwy')) + geom_hisotgram() + ylim(0, 5) """ def __init__(self, low = None, high = None): - if low != None : + if low is not None: try: _ = low - 0 except TypeError: raise Exception("The 'low' argument to", self.__class__.__name__, "must be of a numeric type or None") - if high != None : + if high is not None: try: _ = high - 0 except TypeError: diff --git a/ggplot/ggplot.py b/ggplot/ggplot.py index 09ac1725..231ea886 100755 --- a/ggplot/ggplot.py +++ b/ggplot/ggplot.py @@ -600,7 +600,7 @@ def _prep_layer_for_plotting(self, layer, facetgroup): if 'fill' in self._aes: fillcol_raw = self._aes['fill'][:-5] fillcol = self._aes['fill'] - fill_levels = self.data[[fillcol_raw, fillcol]].sort(fillcol_raw)[fillcol].unique() + fill_levels = self.data[[fillcol_raw, fillcol]].sort_values(by=fillcol_raw)[fillcol].unique() else: fill_levels = None return dict(x_levels=self.data[self._aes['x']].unique(), fill_levels=fill_levels, lookups=df)