suppose I have DataFrame with columns [\'X_Axis\',\'col_2\',\'col_3\',...,\'col_n\',]
I need to plot the first column on X-Axis and rest on Y-Axis. FYI
You need melt for reshape with 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)
Sample:
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)
EDIT: In new versions of seaborn get warning:
The
factorplot
function has been renamed tocatplot
. The original name will be removed in a future release. Please update your code. Note that the defaultkind
infactorplot
('point'
) has changed'strip'
incatplot
.
So use seaborn.catplot, if need same behaviour use kind='point'
:
df = df.melt('X_Axis', var_name='cols', value_name='vals')
g = sns.catplot(x="X_Axis", y="vals", hue='cols', data=df, kind='point')
in addition to mighty @jezrael for those who come from google if you intend to plot lines with the index of the original dataframe just do as follows:
df = pd.DataFrame({'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]})
# resetting index before melting to save the current index in 'index' column...
df = df.reset_index().melt('index', var_name='cols', value_name='vals')
g = sns.catplot(x="index", y="vals", hue='cols', data=df, kind='point')