Highlight multiple Pandas DataFrame columns with Seaborn

Question

Suppose I have a DataFrame with columns ['X_Axis','col_2','col_3',...,'col_n',]

I need to build the first column on the X axis and rely on the Y axis. FYI: all values ​​were grouped according to X-Axis, X-Axis values ​​vary from 0-25, and all other column values ​​were normalized to the scale 0 - 1. I want it on one chart, not in the subtitles.

Preferred: FactorPlot, normal line graph.

Answer 1

You need meltto change using seaborn.factorplot :

df = df.melt('X_Axis', var_name='cols', value_name='vals')
#alternative for pandas < 0.20.0
#df = pd.melt(df, 'X_Axis', var_name='cols',  value_name='vals')
g = sns.factorplot(x="X_Axis", y="vals", hue='cols', data=df)

Example:

df = pd.DataFrame({'X_Axis':[1,3,5,7,10,20],
                   'col_2':[.4,.5,.4,.5,.5,.4],
                   'col_3':[.7,.8,.9,.4,.2,.3],
                   'col_4':[.1,.3,.5,.7,.1,.0],
                   'col_5':[.5,.3,.6,.9,.2,.4]})

print (df)
   X_Axis  col_2  col_3  col_4  col_5
0       1    0.4    0.7    0.1    0.5
1       3    0.5    0.8    0.3    0.3
2       5    0.4    0.9    0.5    0.6
3       7    0.5    0.4    0.7    0.9
4      10    0.5    0.2    0.1    0.2
5      20    0.4    0.3    0.0    0.4

df = df.melt('X_Axis', var_name='cols',  value_name='vals')
g = sns.factorplot(x="X_Axis", y="vals", hue='cols', data=df)