I just want to check if a single cell in Pandas series is null or not i.e. to check if a value is NaN
.
All other answers are for series and arrays, but not for single value.
I have tried pandas.notnull
, pandas.isnull
, numpy.isnan
. Is there a solution for a single value only?
Try this:
import pandas as pd
import numpy as np
from pandas import *
>>> L = [4, nan ,6]
>>> df = Series(L)
>>> df
0 4
1 NaN
2 6
>>> if(pd.isnull(df[1])):
print "Found"
Found
>>> if(np.isnan(df[1])):
print "Found"
Found
STEP 1.)
df[df.isnull().any(1)]
---->
Will give you dataframe with rows and column, if any value there is nan.
STEP 2.)
this will give you location in dataframe where exactly value is nan.
then you could do
if(**df.iloc[loc_row,loc_colum]==np.nan**):
print"your code here"
You can use "isnull" with "at" to check a specific value in a dataframe.
For example:
import pandas as pd
import numpy as np
df = pd.DataFrame([[np.nan, 2], [1, 3], [4, 6]], columns=['A', 'B'])
Yeilds:
A B
0 NaN 2
1 1.0 3
2 4.0 6
To check the values:
pd.isnull(df.at[0,'A'])
-> True
pd.isnull(df.at[0,'B'])
-> False