Python : NaN value in Pandas for a single value only

问题

I just want to check if a single cell in Pandas series is null or not.

i.e, I'd like 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?

回答1:

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

回答2:

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"

回答3:

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

来源：https://stackoverflow.com/questions/27754891/python-nan-value-in-pandas-for-a-single-value-only