pandas-plots 0.7.1

A collection of helper for table handling and vizualization

pandas-plots

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)

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)

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

dependencies