CODEWITHSUNDEEP
pythonpandas
Atihska
Atihska

Reputation: 5126

How to do exact string match while filtering from pandas dataframe

I have a dataframe as

df

   indx   pids
    A    181718,
    B     31718,
    C      1718, 
    D    1235,3456
    E    890654,

I want to return a row that matches 1718 exactly.

I tried to do this but as expected it returns rows where the 1718 is subset as well:

group_df = df.loc[df['pids'].astype(str).str.contains('{},'.format(1718)), 'pids']

   indx   pids
    A    181718,
    B     31718,
    C      1718,

When I try to do something like this, it returns empty: 

cham_geom = df.loc[df['pids'] == '1718', 'pids']

Expected output: 

 indx   pids
  C      1718,

Can anyone help me with it?

Upvotes: 5

Views: 2460

Answers (3)

Ijaz Ur Rahim
Ijaz Ur Rahim

Reputation: 408

there is a method isin that matches and returns a dataframe containing True for matched and false for not matching.

Consider the following example

>>> found = df.isin(["1718,"])==True
>>> df[found].head(3)

this will show the first 3 values matched with 1718

or if you want to match it with only 1 value then you can do so

>>> found = df.pids == "1718,"
>>> df[found].head(3)

Upvotes: 2

ALollz
ALollz

Reputation: 59549

Use str.contains with a negative lookbehind, to ensure there are no other digits before '1718'

Sample Data

import pandas as pd
d = {'indx': {0: 'A', 1: 'B', 2: 'C', 3: 'D', 4: 'E', 5: 'F', 6: 'G'},
     'pids': {0: '181718,', 1: '31718,', 2: '1718,', 3: '1235,3456', 4: '890654,', 5: '1231,1718', 6: '1231, 1718'}}
df = pd.DataFrame(d)

Code:

df.loc[df.pids.str.contains('(?<![0-9])1718')]

Output:

  indx        pids
2    C       1718,
5    F   1231,1718
6    G  1231, 1718

Upvotes: 1

anky
anky

Reputation: 75080

you can try with:

df[df.pids.replace('\D','',regex=True).eq('1718')]

  indx   pids
2    C  1718,

'\D' : Any character that is not a numeric digit from 0 to 9.

EDIT Considering the below df:

  indx       pids
0    A    181718,
1    B     31718,
2    C      1718,
3    D  1235,3456
4    E    890654,
5    F  3220,1718

executing:

df[df.pids.str.split(",").apply(lambda x: '1718' in x)]
#if not comma only:-> df[df.pids.str.split("\D").apply(lambda x: '1718' in x)]

Gives:

  indx       pids
2    C      1718,
5    F  3220,1718

Upvotes: 5

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