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@@ -36,28 +59,28 @@ If you run into the following issue on Mac OS X (or macOS) when importing `plot_
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please follow this solution to fix the issue: https://stackoverflow.com/a/21789908/8892243
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## API documentations
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## 2. API documentations
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All API documentations are on: https://python-plot-utils.readthedocs.io/en/stable/index.html.
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## Current functionalities
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## 3. Current functionalities
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Current functionalities include (for full list, use `print(plot_utils.__doc__)`):
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#### 1. Visualizing one column of data
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###3.1. Visualizing one column of data
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-**Pie chart**: proportions of distinct values in an array, more convenient than matplotlib's `pie()` function [[doc](https://python-plot-utils.readthedocs.io/en/stable/api_docs/pie_chart.html)], [[example](./examples/Pie_chart_example.ipynb)]
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-**Discrete histogram**: counts of distinct values in an array [[doc](https://python-plot-utils.readthedocs.io/en/stable/api_docs/discrete_histogram.html)], [[example](./examples/Discrete_histogram_example.ipynb)]
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#### 2. Visualizing two columns of data ([[example](./examples/Two_columns_of_data_example.ipynb)])
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###3.2. Visualizing two columns of data ([[example](./examples/Two_columns_of_data_example.ipynb)])
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-**"Bin-and-mean" plot**: for two continuous variables [[doc](https://python-plot-utils.readthedocs.io/en/stable/api_docs/bin_and_mean.html)]
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-**Category mean**: for a categorical variable and a continuous variable [[doc](https://python-plot-utils.readthedocs.io/en/stable/api_docs/category_means.html)]
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-**Positive rate**: for a categorical variable and a binary categorical variable [[doc](https://python-plot-utils.readthedocs.io/en/stable/api_docs/positive_rate.html)]
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-**Contingency table**: for two categorical variables [[doc](https://python-plot-utils.readthedocs.io/en/stable/api_docs/contingency_table.html)]
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#### 3. Visualizing multiple columns of data
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###3.3. Visualizing multiple columns of data
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+**3D histograms**: distributions of multiple variables [[doc](https://python-plot-utils.readthedocs.io/en/stable/api_docs/3d_histograms.html)], [[example](./examples/3D_histograms_example.ipynb)]
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+**Multiple histograms**: distribution of multiple variables [[doc](https://python-plot-utils.readthedocs.io/en/stable/api_docs/hist_multi.html)], [[example](./examples/Violin_plot_and_hist_multi_example.ipynb)]
@@ -67,18 +90,18 @@ Current functionalities include (for full list, use `print(plot_utils.__doc__)`)
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+**Count missing values**: how many missing values are there in each column of the dataset [[doc](https://python-plot-utils.readthedocs.io/en/stable/api_docs/missing_values.html)], [[example](./examples/Missing_value_count_example.ipynb)]
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#### 4. Map plotting
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###3.4. Map plotting
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+**Choropleth map** (a.k.a., "heat map") of the United States, on both the state and county level [[doc](https://python-plot-utils.readthedocs.io/en/stable/api_docs/choropleth_map.html)], [[example](./examples/Choropleth_map_example.ipynb)]
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#### 5. Time series plotting
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###3.5. Time series plotting
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-**Plot single time series**: [[doc](https://python-plot-utils.readthedocs.io/en/stable/api_docs/plot_time_series.html)], [[example](./examples/Plot_time_series_example.ipynb)]
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-**Plot multiple time series**: [[doc](https://python-plot-utils.readthedocs.io/en/stable/api_docs/plot_multiple_timeseries.html)], [[example](./examples/Plot_time_series_example.ipynb)]
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-**Fill time series with error bounds**: [[doc](https://python-plot-utils.readthedocs.io/en/stable/api_docs/fill_timeseries.html)], [[example](./examples/Plot_time_series_example.ipynb)]
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#### 6. Miscellaneous
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###3.6. Miscellaneous
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+ A **get_colors()** function that conveniently queries different color palettes [[doc](https://python-plot-utils.readthedocs.io/en/stable/api_docs/get_colors.html)], [[example](./examples/Color_and_linespec_examples.ipynb)]
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+ A **get_linespecs()** function that generates distinct color/linestyle/linewidth combinations for plotting many lines together [[doc](https://python-plot-utils.readthedocs.io/en/stable/api_docs/get_linespecs.html)], [[example](./examples/Color_and_linespec_examples.ipynb)]
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+**visualize_cv_scores()**, which visualizes cross-validation training/evaluation scores [[doc](https://python-plot-utils.readthedocs.io/en/stable/api_docs/visualize_cv_scores.html)], [[example](./examples/Visualize_cross_validation_results.ipynb)]
+ PIL (only if you want to use `trim_img()` or `pad_img()`)
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## Testing
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## 6. Testing
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To test `plot_utils`, run the ipython notebooks in the `examples` folder.
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## Aesthetics
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## 7. Aesthetics
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The aesthetics of of the `plot_utils` module are matplotlib-styled by default, but it doesn't mean that you can't use your favorite styles in seaborn or ggplot2.
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Unlike some plotting packages that enforces their own styles and restrict users from customizing, users of this module can adjust the figure styles freely: either from within matplotlib (https://matplotlib.org/devdocs/gallery/style_sheets/style_sheets_reference.html), or `import seaborn` and let seaborn take care of everything.
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## References
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## 8. References
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I did not built every function of this module entirely from scratch. I documented the sources that I referenced in the documentation of the corresponding functions.
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