CODEWITHSUNDEEP
pythonpandasdataframedescribe
Zahra
Zahra

Reputation: 7207

How to describe columns as categorical values?

I have a pandas dataframe that contains a mix of categorical and numeric columns. By default, df.describe() returns only a summary of the numerical data (describing those columns with count, mean, std, min, quantiles, max)

when iterating through all the columns in the df and describing them individually as [df[c].describe() for c in df.columns] the description is returned based off of specific column dtype; i.e. numerical summary for int and float and categoric summary for object

Does any one know of a succinct way of describing all columns as categorical with count, unique, top, freq?

Upvotes: 13

Views: 21197

Answers (3)

Saurav
Saurav

Reputation: 183

Additionally, if YOU want to see descriptions of all columns together(including categorical). you can use:

df.describe(include='all')

Upvotes: 0

IndPythCoder
IndPythCoder

Reputation: 753

a slightly shorter version of the answer:

df.describe(include = 'object')

Upvotes: 15

Zahra
Zahra

Reputation: 7207

following converts all columns to object type then describes them:

df.astype('object').describe()

for cleaner view try:

df.astype('object').describe().transpose()

Upvotes: 13

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