how to filter string with regular expression in pandas dataframes

Question

import pandas as pd
data = [['Alex',10],['Bob',12],['Clarke',13] ['Adam', 14]]
df = pd.DataFrame(data,columns=['Name','Age'])
print(df)

    Name    Age
0   Alex    10
1   Bob     12
2   Clarke  13
3   Adam    14

I want to get only Names starting with A . I tried following code mask = df['Name'].str.contains("A*")

 mask
 0    True
 1    True
 2    True
 Name: Name, dtype: bool 

 df = df[mask]

   Name    Age

0    Alex    10
1   Bob      12
2   Clarke   13

but I want to get the result as Name Age

0    Alex    10

Missing a comma in your data: data = [['Alex',10],['Bob',12],['Clarke',13], ['Adam', 14]] — DocOc
– DocOc, Commented Sep 17, 2024 at 23:53

Ashish Acharya · Accepted Answer · 2018-07-17 18:14:10Z

4

Use this:

mask = df['Name'].str.startswith("A")

For example:

In [52]: df
Out[52]: 
     Name  Age
0    Alex   10
1     Bob   12
2  Clarke   13
3    Adam   14

In [53]: mask = df['Name'].str.startswith("A")

In [54]: df[mask]
Out[54]: 
   Name  Age
0  Alex   10
3  Adam   14

For regular expression matching, as suggested by @swiftg:

mask = df['Name'].str.match("^A.*")

edited Jul 17, 2018 at 18:14

answered Jul 17, 2018 at 18:09

Ashish Acharya

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4 Comments

TECHI Over a year ago

Also, I want to check for regular expressions like A, * , how to handle such cases

swiftg Over a year ago

mask = df['Name'].str.match("^A.*") for regular expression matching.

swiftg Over a year ago

@TECHI, * matching is "glob" matching, different from regex. Please look it up.

TECHI Over a year ago

how to handle only * is input then?

DocOc · Accepted Answer · 2024-09-17 23:57:46Z

0

Your question asks about using a regular expression (see comment by swftg in first, non-regexp answer). On string columns, Pandas provides the match() method to use matching with regular expressions.

So, for the example you give above, if you want to find all names that start with "A", you would need a mask like:

mask = df['Name'].str.match('^A.*')

If I examine df[mask] I get:

    Name    Age
0   Alex    10
3   Adam    14

answered Sep 17, 2024 at 23:57

DocOc

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