pandas DataFrame - isna() and notna() method | pandas isna & notna example

In this pandas tutorial, we will discuss about:

• isna in pandas dataframe,
• pandas isna example,
• notna in pandas,
• pandas notna example, 

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Lets create a pandas dataframe first and then use it in pandas isna example and pandas notna example.

 

Pandas dataframe is an two dimensional data structure that will store data in two dimensional format. One dimension refers to a row and second dimension refers to a column, So It will store the data in rows and columns.

We can able to create this DataFrame using DataFrame() method. But this is available in pandas module, so we have to import pandas module.

Syntax:

pandas.DataFrame(data)

Where, data is the input dataframe, the data can be a dictionary that stores list of values with specified key.

None / NaN refers to Not a number or empty value. In python we can create na by using None keyword or numpy.nan.

 

Example: create dataframe

In this example, we will create a dataframe with 4 rows and 4 columns with college data and assign indices through index parameter. We are including some numpy.nan values. We have to import numpy module to create nan values.

import pandas as pd
import numpy as np

#create dataframe from the college data
data= pd.DataFrame({'college_id':['c-001',np.nan,'c-002','c-004'],

                    'college_name':["vignan university","vvit","RVR - JC","Andhra University"],

                   "college_address":[np.nan,"guntur","guntur","guntur"],

                    "Total Staff":[1200,np.nan,np.nan,670]

                   },index=['one','two','three','four'])

#display the dataframe
print(data)

Output: dataframe is created below

      college_id       college_name college_address  Total Staff
one        c-001  vignan university            None       1200.0
two         None               vvit          guntur          NaN
three      c-002           RVR - JC          guntur          NaN
four       c-004  Andhra University          guntur        670.0

 

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isna in pandas dataframe

isna() method or isna in pandas dataframe is used to check the value is nan or not. If the value is nan then it will return True, otherwise False in the DataFrame.

Syntax:

dataframe.isna()

where, dataframe is the input dataframe

 

Example: pandas isna example

In this pandas isna example, we are going to check whether the values are nan or not using isna() method.

import pandas as pd

#create dataframe from the college data
data= pd.DataFrame({'college_id':['c-001',None,'c-002','c-004'],

                    'college_name':["vignan university","vvit","RVR - JC","Andhra University"],

                   "college_address":[None,"guntur","guntur","guntur"],

                    "Total Staff":[1200,None,None,670]

                   },index=['one','two','three','four'])

#check the data in the dataframe are nan or not
print(data.isna())

Output: pandas isna example result

       college_id  college_name  college_address  Total Staff
one         False         False             True        False
two          True         False            False         True
three       False         False            False         True
four        False         False            False        False

Lets now see how to use notna in pandas.

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notna in pandas

notna() method or notna in pandas is used to check the value is nan or not. If the value is nan then it will return False, otherwise True in the DataFrame.

Syntax:

dataframe.notna()

where, dataframe is the input dataframe

 

Example: pandas notna example

In this pandas notna example, we are going to check whether the values are nan or not using notna() method.

import pandas as pd

#create dataframe from the college data
data= pd.DataFrame({'college_id':['c-001',None,'c-002','c-004'],

                    'college_name':["vignan university","vvit","RVR - JC","Andhra University"],

                   "college_address":[None,"guntur","guntur","guntur"],

                    "Total Staff":[1200,None,None,670]

                   },index=['one','two','three','four'])

#check the data in the dataframe are nan or not
print(data.notna())

Output: pandas notna example result

       college_id  college_name  college_address  Total Staff
one          True          True            False         True
two         False          True             True        False
three        True          True             True        False
four         True          True             True         True

Thus we come to end of our chapter on isna in pandas dataframe & notna in pandas along with proper example.