CODEWITHSUNDEEP
pythonpandassorting
user9410826
user9410826

Reputation:

How to select specific rows in a pandas df

I am trying to sort a pandas df based on specific values. So for the pandas df below I want to select values A, C in Column Event. I also want to select values U,Z in Column Code

import pandas as pd

d = ({
    'Event' : ['A','B','C','D','E','A','B','C','D'],
    'Code' : ['W','X','Y','U','Z','X','Y','W','Z'],
    'Int' : [1,2,3,4,5,6,7,8,9]
    })

df = pd.DataFrame(data = d)

I can do it via one column:

df = df.loc[df['Event'].isin(['A','C'])]

But if I try to include the second Column

df = df.loc[df['Code'].isin(['U','Z'])]

It returns an empty df. My intended df is:

  Event Code  Int
0     A    W    1
1     C    Y    3
2     D    U    4
3     E    Z    5
4     A    X    6
5     C    W    8
6     D    Z    9

Upvotes: 1

Views: 1988

Answers (4)

Aps
Aps

Reputation: 264

Here you can call both values from diferent colums at the same time.

new_df=df[(df["event"] == 'A') & (df["code"] == "u") ]

Upvotes: 0

javaShilp
javaShilp

Reputation: 59

What's happening here is u are first selecting the rows with A,C and in that u are trying to search for columns with U and Z. But if you notice, none of the rows with A,C in Event have a value of U and Z in code column. That is the reason you are getting an empty dataframe.

Try the below: 

 newdf = df.query("Event in ['A','C'] | Code in ['U','Z']")
 newdf



    Event Code  Int
0     A    W    1
2     C    Y    3
3     D    U    4
4     E    Z    5
5     A    X    6
7     C    W    8
8     D    Z    9

Upvotes: 1

msr_003
msr_003

Reputation: 1233

One possible solution.

df[(df.Code.isin(['U','Z'])) | (df.Event.isin(['A', 'C']))]

Upvotes: 0

Joe
Joe

Reputation: 12417

I think you need:

df = df.loc[df['Event'].isin(['A','C']) | df['Code'].isin(['U','Z'])].reset_index(drop=True)

Output:

  Code Event  Int
0    W     A    1
1    Y     C    3
2    U     D    4
3    Z     E    5
4    X     A    6
5    W     C    8
6    Z     D    9

Upvotes: 2

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