Assign a variable to none if the resulting dataframe is empty after filtering columns

Question

I'm trying to get values in column z that contains null values or integers:

df = pd.DataFrame({'X': [1, 2, 3, 4],
                    'Y': [2, 10, 13, 18],
                  'Z': [3, None, 5, None]})

a = df[(df.X == 1) & (df.Y == 2)].Z.item()
print(a)
#output: 3

b = df[(df.X == 7) & (df.Y == 18)].Z.item()
print(b)
#output: error

It throws a value error: can only convert an array of size 1 to a Python scalar. Because the data frame resulting from filtering the X and Y columns is empty. I want to assign variable b to None if the data frame is empty.

I tried the following, and it works:

#checking the length of the dataframe
b = df[(df.X == 1) & (df.Y == 2)].Z.item() if (len(df[(df.X == 7) & (df.Y == 18)]) == 1) else None
print(b)
# output: None

Is there a better way to do it?

akuiper · Accepted Answer · 2022-11-25 20:01:15Z

1

One alternative is to use next(..., None), which returns None if the iterator is empty:

b = next(iter(df[(df.X == 7) & (df.Y == 18)].Z), None)
print(b)
# None

answered Nov 25, 2022 at 20:01

akuiper

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Comments

Georgina Skibinski · Accepted Answer · 2022-11-25 20:09:29Z

0

2 things - your result is empty, hence error - .item() apparently throws an error on empty pd.Series. Secondly - the more canonical way of achieving what you're after would be:

>>> b = df.loc[(df.X == 7) & (df.Y == 18), "Z"].values
>>> if len(b) == 0: b=None
...

Also prevents error .item() generates.

edited Nov 25, 2022 at 20:09

answered Nov 25, 2022 at 20:01

Georgina Skibinski

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4 Comments

M J Over a year ago

This does not assign the variable b to None but to an empty array.

Georgina Skibinski Over a year ago

which is correct - since 0 rows match your filtering criteria.

M J Over a year ago

I do want it to be assigned to None if 0 rows match your filtering criteria

Georgina Skibinski Over a year ago

just add if statement - see my edit.

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