How to find each row and column data type in pandas dataframe using apply, map or applymap?-CodePudding

I have dataframe as shown in image. I want each row and columns data type using apply/map/applymap. How to get this datatype? Some columns have mixed datatype as highlighted e.g. list and str, some have list and dict.

[![samplepandasdataframe][1]][1]

[1]:

CodePudding user response：

If you want to have the evaluated type value of every cell you can use

def check_type(x):
     try: 
        return type(eval(x)) 
     except Exception as e:
        return type(x)

df.applymap(check_type)

If you want to also get how many datatypes you have you can use things like

df.applymap(type).value_counts()

or if you want to get the values for all of the dataframe instead of by column

np.unique(df.applymap(type).astype(str).values, return_counts=True)