Querying for NaN and other names in Pandas

Question

Say I have a dataframe df with a column value holding some float values and some NaN. How can I get the part of the dataframe where we

Answer 1

You can use the isna and notna Series methods, which is concise and readable.

import pandas as pd
import numpy as np

df = pd.DataFrame({'value': [3, 4, 9, 10, 11, np.nan, 12]})
available = df.query("value.notna()")
print(available)

#    value
# 0    3.0
# 1    4.0
# 2    9.0
# 3   10.0
# 4   11.0
# 6   12.0

not_available = df.query("value.isna()")
print(not_available)

#    value
# 5    NaN

Alternatively, you can use the toplevel pd.isna function, by referencing it as a local variable.

import pandas as pd
import numpy as np


df = pd.DataFrame({'value': [3, 4, 9, 10, 11, np.nan, 12]})
df.query("@pd.isna(value)")

#    value
# 5    NaN