Python.pandas: how to select rows where objects start with letters 'PL'

Question

I have specific problem with pandas: I need to select rows in dataframe which start with specific letters. Details: I've imported my data to dataframe and selected columns that I need. I've also narrowed it down to row index I need. Now I also need to select rows in other column where objects START with letters 'pl'.

Is there any solution to select row only based on first two characters in it?

I was thinking about

pl = df[‘Code’] == pl*

but it won't work due to row indexing. Advise appreciated!

This is a duplicate of Select rows if string begins with certain characters in pandas — Trenton McKinney
– Trenton McKinney, Commented Jun 15, 2020 at 21:29

NYC Coder · Accepted Answer · 2020-06-15 21:18:05Z

24

Use startswith for this:

df = df[df['Code'].str.startswith('pl')]

answered Jun 15, 2020 at 21:18

NYC Coder

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Comments

thibaultbl · Accepted Answer · 2020-12-30 08:55:38Z

5

Fully reproducible example for those who want to try it.

import pandas as pd

df = pd.DataFrame([["plusieurs", 1], ["toi", 2], ["plutot", 3]])

df.columns = ["Code", "number"]

df = df[df.Code.str.startswith("pl")] # alternative is df = df[df["Code"].str.startswith("pl")]

edited Dec 30, 2020 at 8:55

answered Sep 30, 2020 at 6:50

thibaultbl

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Comments

azro · Accepted Answer · 2020-06-15 21:21:59Z

3

The condition is just a filter, then you need to apply it to the dataframe. as filter you may use the method Series.str.startswith and do

df_pl = df[df['Code'].str.startswith('pl')]

edited Jun 15, 2020 at 21:21

answered Jun 15, 2020 at 21:21

azro

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1 Comment

Trenton McKinney Over a year ago

This is the same as the other answer.

azro · Accepted Answer · 2020-09-30 06:40:15Z

2

If you use a string method on the Series that should return you a true/false result. You can then use that as a filter combined with .loc to create your data subset.

new_df = df.loc[df[‘Code’].str.startswith('pl')].copy()

edited Sep 30, 2020 at 6:40

azro

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answered Jun 15, 2020 at 21:31

Mike

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