pandas-plots-0.8.0.tar.gz

# pandas-plots     ## usage install / update package ```bash pip install pandas-plots -U ``` include in python ```python from pandas_plots import tbl, plt, ven ``` ## example ```python # load sample dataset from seaborn import seaborn as sb df = sb.load_dataset('taxis') plt.plot_box(df['fare'], height=400, violin=True) ```  ## why use pandas-plots `pandas-plots` is a package to help you examine and visualize data that are organized in a pandas DataFrame. It provides a high level api to pandas / plotly with some selected functions. It is subdivided into: - `tbl` utilities for table descriptions - `describe_df()` an alternative version of pandas `describe()` function - `pivot_df()` gets a pivot table of a 3 column dataframe - `plt` for plotly visualizations - `plot_box()` auto annotated boxplot w/ violin option - `plot_boxes()` multiple boxplots _(annotation is experimental)_ - `plots_bars()` a standardized bar plot - `plot_stacked_bars()` shortcut to stacked bars ���� - `plot_quadrants()` quickly shows a 2x2 heatmap - `ven` offers functions for _venn diagrams_ - `show_venn2()` displays a venn diagram for 2 sets - `show_venn3()` displays a venn diagram for 3 sets - `sql` is added as convienience wrapper for retrieving data from sql databases - `connect_sql` get data from `['mssql', 'sqlite','postgres']` ## more examples ```python # quick and exhaustive description of any table tbl.describe_df(df, 'taxis', top_n_uniques=5) ```  ```python # show pivoted values for selected columns tbl.pivot_df(df[['color', 'payment', 'fare']]) ```  ```python # show venn diagram for 3 sets from pandas_plots import ven set_a = set(df.pickup_zone) set_b = set(df.dropoff_zone) set_c = set(df['pickup_borough']) _df, _details = ven.show_venn3( "taxis", set_a, "pick", set_b, "drop", c_set=set_c, c_label="borough", verbose=0, size=8, ) ```  ## dependencies