pdpatch
pdpatch adds methods to pandas’
DataFrame and Series for a faster data science pipeline. It also
defines drop-in replacements for seaborn and plotly.express that
automatically label axes with nicer titles. We use
nbdev to build this project.
Install
pip install pdpatch
How to use
from pdpatch.all import *
Interactive Method .less()
Automatically Rename snake_case columns in plotly.express and seaborn
import pandas as pd
from pdpatch.express import *
df = pd.DataFrame({'time__s__': range(10), 'position__m__': [i**1.3 for i in range(10)], 'speed__m/s__': 10*[1]})
#df = pd.DataFrame({'time__s__': range(10), 'position__m__': range(10)})
px.scatter(df, x='time__s__', y='position__m__').show('png')
from pdpatch.seaborn import sns
sns.scatterplot(data=df, x='time__s__', y='position__m__');
Add Altair-like Operation to plotly Figures
fig = px.scatter(df,x='time__s__', y='time__s__') | px.scatter(df,x='time__s__', y=['position__m__', 'speed__m/s__'])
fig.show('png')
fig = px.scatter(df,x='time__s__', y='time__s__') / px.scatter(df,x='time__s__', y=['position__m__', 'speed__m/s__'])
fig.show('png')
fig = px.scatter(df,x='time__s__', y='time__s__') | px.scatter(df,x='time__s__', y=['position__m__', 'speed__m/s__'])
(fig / fig).show('png')
Shorter methods
df.rename(columns={'col_1': 'new_name'})->df.renamec('col_1', 'new_name')
df = dummydf()
df.renamec('col_1', 'new_name').to_html()| new_name | col_2 | |
|---|---|---|
| 0 | 100 | a |
| 1 | 101 | b |
| 2 | 102 | c |
| 3 | 103 | d |
| 4 | 104 | e |
Functions as methods
df.len()5
New methods
df.col_1.minmax(100, 104)
Utility functions
df = dummydf()
df.to_html()| col_1 | col_2 | |
|---|---|---|
| 0 | 100 | a |
| 1 | 101 | b |
| 2 | 102 | c |
| 3 | 103 | d |
| 4 | 104 | e |
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