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‘if’ statement in filter() method
Question about the filter() method in Pandas.
I have the following code:
import pandas as pd
import numpy as np
df1 = pd.DataFrame({“type”: [“A”, “B”],
“value”: [1, 2]})
df2 = pd.DataFrame({“type”: [“A”, “B”],
“value”: [3, 4]})
df3 = pd.DataFrame({“type”: [“A”, “C”],
“value”: [5, 6]})
df4 = pd.DataFrame({“type”: [“A”, “C”],
“value”: [7, 8]})
df = pd.concat([df1, df2, df3, df4])
df = df.set_index([‘type’])
df = df.groupby(level=1).filter(lambda d: d[‘value’]>d[‘value’].shift().bfill()).copy()
And I get this output:
value
type
A 1.0
a2fa7ad3d0
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