Supporting Statistical Analysis for Research

3.2 Relationship between two continuous variables

1. Import the Mroz.csv data set.

   from pathlib import Path
   import pandas as pd
   import plotnine as p9

   mroz_path = Path('..') / 'datasets' / 'Mroz.csv'
   mroz = pd.read_csv(mroz_path)
   
   print(mroz.dtypes)

   Unnamed: 0      int64
   lfp            object
   k5              int64
   k618            int64
   age             int64
   wc             object
   hc             object
   lwg           float64
   inc           float64
   dtype: object

3.2.0.1 Exploring - Scatter plots

1. Plot inc against lwg.

   print(
       p9.ggplot(mroz, p9.aes(x='lwg', y='inc')) + 
       p9.geom_point() +
       p9.theme_bw())

   <ggplot: (143589751830)>

   

2. Plot age against lwg. Add a loess line to the plot.

   print(
       p9.ggplot(mroz, p9.aes(x='lwg', y='age')) + 
       p9.geom_point() +
       p9.geom_smooth(color='blue') +
       p9.theme_bw())

   <ggplot: (-9223371893264592275)>
   
   C:\PROGRA~3\ANACON~1\lib\site-packages\plotnine\stats\smoothers.py:146: UserWarning: Confidence intervals are not yet implementedfor lowess smoothings.
     warnings.warn("Confidence intervals are not yet implemented"