Creating column with datatypes with pandas

Question

I have a DataFrame df:

A   B
1   dog 
cat XX

I have been trying to create a pandas DataFrame df_new that looks like this:

A   B    type_of_A   type_of_B
1   dog  int         string
cat XX   string      whateverdtype it may be

I tried with:

df_new["type_of_A"] = [pd.api.types.infer_dtype(i) for i in range(df_new['A'].values)]

But I only got:

TypeError: only integer scalar arrays can be converted to a scalar index

Can anyone give me a hint? is this the right approach?

Thanks so much in advance

BENY · Accepted Answer · 2019-03-18 16:00:29Z

3

Using applymap with type, the concat back

s=df.applymap(type).add_prefix('type_of_')
df=pd.concat([df,s],1)
Out[543]: 
     A    B      type_of_A      type_of_B
0    1  dog  <class 'int'>  <class 'str'>
1  cat   XX  <class 'str'>  <class 'str'>

answered Mar 18, 2019 at 16:00

BENY

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2 Comments

iraciv94 Over a year ago

is there a way to apply this procedure to individual columns instead to the whole df? because I believe that "applymap" does not work on series.

BENY Over a year ago

@iraciv94 just do s.apply(type) for series

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