Python Pandas populate column from partial string match

Question

I have a dataframe like below, and I need to create a new column Block with either the value 1 or 2 in it based on a partial string match in the column Program Number where it says _block_1 or _block_2. I've been trying if statements and .str.contains but can't get it to work. How would you do this?

148 0209-3SP_block_1    ['g76p010060q00250r.0005'   'JEBD0507160 REV A' CHNCIII
149 0209-3SP_block_2    ['g76x.3761z-.500p03067q03067f.05'  'JEBD0507160 REV A' CHNC III
150 0209-5SP_block_1    ['g76p020060q00250r.0005'   'JEBD0507160 REV A' CHNC III
151 0209-5SP_block_2    ['g76x.3767z-.48p03067q03067f.05'   'JEBD0507160 REV A' CHNC III
152 0210-3SP_block_1    ['g76p010060q00250r.0005'   'JEBD0507160 REV A' CHNC III

Just tried another method: block1 = df['Machine'].str.contains('_block_1') df['Block'] = block1.replace((True,False), ('1','2')) but this added all 2 to column — Chris Macaluso
– Chris Macaluso, Commented Jan 21, 2019 at 1:22
See https://pandas.pydata.org/pandas-docs/stable/text.html, specifically regex part. — mr_mo
– mr_mo, Commented Jan 21, 2019 at 1:23
Thanks for the link, that's actually what I've been using on this last attempt, the section Testing for Strings that Match or Contain a Pattern — Chris Macaluso
– Chris Macaluso, Commented Jan 21, 2019 at 1:28

Abramodj · Accepted Answer · 2019-01-21 01:33:40Z

1

You could use the method where from numpy:

import numpy as np

df['Block'] = np.where(
    df['Machine'].str.contains('_block_1'),1,
    np.where(df['Machine'].str.contains('_block_2'),2,0)
)

Otherwise, assuming all the strings have the same length:

df['Block'] = df['Machine'].str[15:].astype(int)

answered Jan 21, 2019 at 1:33

Abramodj

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