JuniorTheoryCommon

What does this program print?

Python

import numpy as np
import pandas as pd

df = pd.DataFrame({
    "age": [25, np.nan, 31],
    "city": ["Kazan", None, None],
})
print(df.isna().sum().tolist())

[1, 2]

Expecting [0, 2, 1], a count per row: sum() adds down each column by default, so you get one count per column — 1 for age, 2 for city.
Expecting None in a text column to go uncounted: isna() marks both NaN and None as missing.

How would you count the missing values in each row instead?
How do you get the share of missing values per column rather than the count?

Back to questions Open topic in roadmap →Answer it yourself — Quiz

Back to questions

JuniorTheoryCommon

What does this program print?

Python

import numpy as np
import pandas as pd

df = pd.DataFrame({
    "age": [25, np.nan, 31],
    "city": ["Kazan", None, None],
})
print(df.isna().sum().tolist())

[1, 2]

Expecting [0, 2, 1], a count per row: sum() adds down each column by default, so you get one count per column — 1 for age, 2 for city.
Expecting None in a text column to go uncounted: isna() marks both NaN and None as missing.

How would you count the missing values in each row instead?
How do you get the share of missing values per column rather than the count?

Back to questions Open topic in roadmap →Answer it yourself — Quiz