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A collection of helper for table handling and vizualization

Project description

pandas-plots

PyPI - Version GitHub last commit GitHub License py3.10

usage

install / update package

pip install pandas-plots -U

include in python

from pandas_plots import tbl, viz

example

# load sample dataset from seaborn
import seaborn as sb
df = sb.load_dataset('taxis')

viz.plot_box(df['fare'], height=400, violin=True)

plot_box

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
  • viz utilities 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 show a 2x2 heatmap
  • sql is added as convienience wrapper for fetching data from sql databases

    • connect_sql get data from ['mssql', 'sqlite','postgres']

another example

# quick and exhaustive description of any table
tbl.describe_df(df, 'taxi', top_n_uniques=5)

describe_df

# show pivoted values for selected columns
tbl.pivot_df(df[['color', 'payment', 'fare']])

pivot_df

dependencies

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