12.3.4.2. Missing data

import pandas as pd
import numpy as np


dates = pd.date_range("20220501", periods=6)
dataFrame = pd.DataFrame(np.random.randn(6, 4), index=dates, columns=list("ABCD"))

Missing data

dataFrame1 = dataFrame.reindex(index=dates[0:4], columns=list(dataFrame.columns) + ["E"])
dataFrame1.loc[dates[0] : dates[1], "E"] = 1

dataFrame1.dropna(how="any")

	A	B	C	D	E
2022-05-01	1.182016	-1.120701	-0.676976	0.409597	1.0
2022-05-02	-0.178852	-0.790282	0.121684	-1.552807	1.0

dataFrame1.fillna(value=5)

	A	B	C	D	E
2022-05-01	1.182016	-1.120701	-0.676976	0.409597	1.0
2022-05-02	-0.178852	-0.790282	0.121684	-1.552807	1.0
2022-05-03	-0.796187	0.844108	-1.278492	-0.813399	5.0
2022-05-04	0.555198	1.362921	-0.235213	-0.096281	5.0

pd.isna(dataFrame1)

	A	B	C	D	E
2022-05-01	False	False	False	False	False
2022-05-02	False	False	False	False	False
2022-05-03	False	False	False	False	True
2022-05-04	False	False	False	False	True