A collection of helper for table handling and vizualization
Project description
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 descriptionsdescribe_df()
an alternative version of pandasdescribe()
functionpivot_df()
gets a pivot table of a 3 column dataframe
-
viz
utilities for plotly visualizationsplot_box()
auto annotated boxplot w/ violin optionplot_boxes()
multiple boxplots (annotation is experimental)plots_bars()
a standardized bar plotplot_stacked_bars()
shortcut to stacked bars 😄plot_quadrants()
quickly show a 2x2 heatmap
-
sql
is added as convienience wrapper for fetching data from sql databasesconnect_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
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