Python 3.x: function to determine missing values

Question

I have the following data:

import pandas as pd

data = {'var1': ['pero03930', 'pero03930', ' '],
        'var2': ['121324', '232434', ' '],
        'var3': [343, 937, 989],
        }

df = pd.DataFrame (data, columns = ['var1', 'var2', 'var3'])

print(df)

I'm trying to develop a function that identifies the missing values and this is what I have so far:

def missing_values(var1, var2, var3):
    if var1 is None:
        return 'Missing var1 in data'
    if var2 is None:
        return 'Missing var2 in data'
    if var3 is None:
        return 'missing var3 value in data'
    else:
        return 'No missing values in data'

print(missing_values(df))

I get this error:

TypeError: missing_values1() missing 2 required positional arguments: 'var2' and 'var3'

I know this is because the function is trying to find the two other parameters. How do I get the function to recognize that the parameters are within the data set? Or is there generally a better way to write this function?

Does this answer your question? [Find empty or NaN entry in Pandas Dataframe](https://stackoverflow.com/questions/27159189/find-empty-or-nan-entry-in-pandas-dataframe) — Tomerikoo, May 26 '20 at 10:55

PSKP · Accepted Answer · 2020-05-26T10:59:52.360

I believe you should use inbuilt function to find None. And also " " != None

import pandas as pd

data = {'var1':  ['pero03930', 'pero03930', None],
        'var2': ['121324', '232434', ' '],
        'var3': [343, 937, 989],
        }

df = pd.DataFrame (data, columns = ['var1', 'var2', 'var3'])

print(df[df.isnull().any(axis=1)])

output

   var1 var2  var3
2  None  nan   989

Your Code

If you want, your code working then check following code. But your code has lots of problem.

When first None found, it will return. It never find other None in same row

import pandas as pd

data = {'var1':  ['pero03930', 'pero03930', None],
        'var2': ['121324', '232434', ' '],
        'var3': [343, 937, 989],
        }

df = pd.DataFrame (data, columns = ['var1', 'var2', 'var3'])


def missing_values(var1,var2,var3):
    if var1 is None:
        return 'Missing var1 in data'
    if var2 is None:
        return 'Missing var2 in data'
    if var3 is None:
        return 'missing var3 value in data'
    else:
        return 'No missing values in data'

for index, row in df.iterrows():
    print(missing_values(row["var1"], row["var2"], row["var3"]))

Output

No missing values in data
No missing values in data
Missing var1 in data

If this solution solves your problem then accept it else comment what's the problem.

Hi, thanks for this. Can you explain why the code has lots of problems? It doesn't matter that once a null or None is found that it stops searching, I just need to know if there are 1 or more nulls. Using the way you have used the function here does work — Mrmoleje, May 26 '20 at 12:13
If you don't care about other None when one found then your code is OK. If your problem is solved the please accept it. — PSKP, May 26 '20 at 12:53

Python 3.x: function to determine missing values

1 Answers1

output

Your Code

Output