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I have a dataframe with several categorical columns. I know how to do countplot which routinly plots ONE column. Q: how to plot maximum count from ALL columns in one plot?
here is an exemplary dataframe to clarify the question:
import pandas as pd
import numpy as np
import seaborn as sns
testdf=pd.DataFrame(({ 'Ahome' : pd.Categorical(["home"]*10),
'Bsearch' : pd.Categorical(["search"]*8 + ["NO"]*2),
'Cbuy' : pd.Categorical(["buy"]*5 + ["NO"]*5),
'Dcheck' : pd.Categorical(["check"]*3 + ["NO"]*7),
} ))
testdf.head(10)
sns.countplot(data=testdf,x='Bsearch');
The last line is just using normal countplot for one column. I'd like to have the columns category (home,search,buy and check) in x-axis and their frequency in y-axis.
Thanks in advance!
582
In Seaborn, we will plot multiple graphs in a single window in two ways. First with the help of Facetgrid() function and other by implicit with the help of matplotlib. data: Tidy dataframe where each column is a variable and each row is an observation.
Show the counts of observations in each categorical bin using bars. A count plot can be thought of as a histogram across a categorical, instead of quantitative, variable.
To create a horizontal bar chart or countplot in Seaborn, you simply map your categorical variable to the y-axis (instead of the x-axis). When you map the categorical variable to the y-axis, Seaborn will automatically create a horizontal countplot.
You need to use countplot as below:
df = pd.melt(testdf)
sns.countplot(data=df.loc[df['value']!="NO"], x='variable', hue='value')
Output:
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