筛选 pandas dataframe 行，其中具有列 A 和值 X 的特定行具有列 B，其值 Y 大于参数 Z

Question

I wonder if there's a simpler way to filter a pandas DataFrame rows where a specific row with column A and value X has column B with value Y greater than a parameter Z.

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For example:

	A	B
72154	X1	0.998429
72155	X2	0.584253
72156	X3	0.797648
72157	X2	0.981707
72158	X1	0.698844
72159	X3	0.987943
72160	X1	0.797648
72161	X3	0.984621
72162	X2	0.221968

I've managed to get it done with this code:

import pandas as pd

Z = 0.8
mask1 = (df.A.isin(['X1', 'X2']))
mask2 = (df.B > Z)
mask3 = (df.A == 'X3')
sub_df_x1_x2 = df[mask1 & mask2]
sub_df_x3  = df[mask3]
final_df = pd.concat([sub_df_x1_x2, sub_df_x3])

But I don't believe this is the cleanest or best way to do it. Do you guys have any idea? I was thinking about something like this, but I was not able to get it to work.

mask1 = (df.A.isin(['X1', 'X2']) & df.B > Z)
# or
mask1 = (df.A.isin(['X1', 'X2'])[B] > Z)

Answer 1

You could chain the two with |:

out = df[(df.A.isin(['X1', 'X2']) & (df.B > Z)) | (df.A == 'X3')]

or using the definitions you already have:

out = df[(mask1 & mask2) | mask3]

Output:

        A         B
72154  X1  0.998429
72156  X3  0.797648
72157  X2  0.981707
72159  X3  0.987943
72161  X3  0.984621