pythonpandasdataframedescribe

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?

Solution

  • following converts all columns to object type then describes them:

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

    for cleaner view try:

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