How to get datatypes of all columns using a single command [ Python - Pandas ]?

Question

I want to see the datatype of all columns stored in my dataframe without iterating over them. What is the way?

Answer 1

10 min to pandas has nice example for DataFrame.dtypes:

df2 = pd.DataFrame({      'A' : 1.,     'B' : pd.Timestamp('20130102'),     'C' : pd.Series(1,index=list(range(4)),dtype='float32'),     'D' : np.array([3] * 4,dtype='int32'),     'E' : pd.Categorical(["test","train","test","train"]),     'F' : 'foo' })  print (df2)      A          B    C  D      E    F 0  1.0 2013-01-02  1.0  3   test  foo 1  1.0 2013-01-02  1.0  3  train  foo 2  1.0 2013-01-02  1.0  3   test  foo 3  1.0 2013-01-02  1.0  3  train  foo  print (df2.dtypes) A           float64 B    datetime64[ns] C           float32 D             int32 E          category F            object dtype: object 

But with dtypes=object it is a bit complicated (generally, obviously it is string):

Sample:

df = pd.DataFrame({'strings':['a','d','f'],                    'dicts':[{'a':4}, {'c':8}, {'e':9}],                    'lists':[[4,8],[7,8],[3]],                    'tuples':[(4,8),(7,8),(3,)],                    'sets':[set([1,8]), set([7,3]), set([0,1])] })  print (df)       dicts   lists    sets strings  tuples 0  {'a': 4}  [4, 8]  {8, 1}       a  (4, 8) 1  {'c': 8}  [7, 8]  {3, 7}       d  (7, 8) 2  {'e': 9}     [3]  {0, 1}       f    (3,) 

All values have same dtypes:

print (df.dtypes) dicts      object lists      object sets       object strings    object tuples     object dtype: object 

But type is different, if need check it by loop:

for col in df:     print (df[col].apply(type))  0    <class 'dict'> 1    <class 'dict'> 2    <class 'dict'> Name: dicts, dtype: object 0    <class 'list'> 1    <class 'list'> 2    <class 'list'> Name: lists, dtype: object 0    <class 'set'> 1    <class 'set'> 2    <class 'set'> Name: sets, dtype: object 0    <class 'str'> 1    <class 'str'> 2    <class 'str'> Name: strings, dtype: object 0    <class 'tuple'> 1    <class 'tuple'> 2    <class 'tuple'> Name: tuples, dtype: object 

Or first value of columns with iat:

print (type(df['strings'].iat[0])) <class 'str'>  print (type(df['dicts'].iat[0])) <class 'dict'>  print (type(df['lists'].iat[0])) <class 'list'>  print (type(df['tuples'].iat[0])) <class 'tuple'>  print (type(df['sets'].iat[0])) <class 'set'>