DataFrame.dtypes() to get all data types in Pandas

Pandas

dtypes : Returns dtypes of DataFrame.
Here is one DataFrame with 7 types (all) of dtypes.

import pandas as pd 
td = pd.Series([pd.Timedelta(days=i) for i in range(6)])  
my_dict={'NAME':['Ravi','Raju','Alex','Ron','King','Jack'],
         'ID':[1,2,3,4,5,6],
         'MATH':[80,40,70,70,70,30],
         'Avg_mark':[45.5,48.09,50.12,55.1,50.6,55.6],
         'dt_start':['1/1/2020','2/1/2020','5/1/2020','11/7/2020',
			'15/8/2020','31/12/2020'],
         'Exam':[True,False,True,True,False,False],
         'dt':td,
         'grade':['a', 'c', 'b', 'b','b','c']}

my_data = pd.DataFrame(data=my_dict)
my_data['grade']=my_data['grade'].astype('category')
my_data['dt_start'] = pd.to_datetime(my_data['dt_start'])
print(my_data.dtypes)

Output

NAME                 object
ID                    int64
MATH                  int64
Avg_mark            float64
dt_start     datetime64[ns]
Exam                   bool
dt          timedelta64[ns]
grade              category
dtype: object

We can get dtype of particular column.

print(my_data['Avg_mark'].dtypes)

Output

float64

Different Data types ( dtypes )

dtype	Uses	Code
int64	Integer type	'ID':[1,2,3,4,5,6]
float64	Decimal,float	'Avg_mark':[45.5,48.09,50.12,55.1,50.6,55.6]
datetime64[ns]	Date & Time	'dt_start':['1/1/2020','2/1/2020','5/1/2020' ... ]
object	String or mixed	'NAME':['Ravi','Raju','Alex','Ron','King','Jack']
bool	Boolean	'Exam':[True,False,True,True,False,False]
timedelta64[ns]	Timedelta	pd.Series([pd.Timedelta(days=i) for i in range(6)])
category	Categorical	pd.Series(["a", "b", "c", "a"], dtype="category")

Using correct data type is important as our handling of data depends on it. If data type is int64 then we will get output as 4 for 2 + 2 , but we will get 22 as output if data type is object.

You can change the data type by using astype().
We can successfully convert the data types if data matches to new data type. Otherwise we have to clean the data before using astype()
Data Cleaning
Pandas to_timedelta() astype() select_dtypes() timedelta64() categorical data types

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