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, plt, ven
example
# 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:
-
tblutilities for table descriptionsdescribe_df()an alternative version of pandasdescribe()functionpivot_df()gets a pivot table of a 3 column dataframe
-
pltfor 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 shows a 2x2 heatmap
-
venoffers functions for venn diagramsshow_venn2()displays a venn diagram for 2 setsshow_venn3()displays a venn diagram for 3 sets
-
sqlis added as convienience wrapper for retrieving data from sql databasesconnect_sqlget data from['mssql', 'sqlite','postgres']
-
txtincludes some text based utilitieswrapformats strings or lists to a given width to fit nicely on the screen
more examples
# quick and exhaustive description of any table
tbl.describe_df(df, 'taxis', top_n_uniques=5)
# show pivoted values for selected columns
tbl.pivot_df(df[['color', 'payment', 'fare']])
# 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
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