Python Pandas: Check If String in One Column Is Contained in String of Another Column in the Same Row

Python Pandas: Check if string in one column is contained in string of another column in the same row

You need apply with in:

df['C'] = df.apply(lambda x: x.A in x.B, axis=1)
print (df)
   RecID  A    B      C
0      1  a  abc   True
1      2  b  cba   True
2      3  c  bca   True
3      4  d  bac  False
4      5  e  abc  False

Another solution with list comprehension is faster, but there has to be no NaNs:

df['C'] = [x[0] in x[1] for x in zip(df['A'], df['B'])]
print (df)
   RecID  A    B      C
0      1  a  abc   True
1      2  b  cba   True
2      3  c  bca   True
3      4  d  bac  False
4      5  e  abc  False

Pandas: check if string value in one column is part of string of another column in same row of dataframe - current script returning all Yes

In your case

df['Compare'] = df.apply(lambda x: 'Yes' if x['DEPTH'] in x['Description'] else 'No',axis=1)
df
Out[133]: 
    WKEY                                   Description DEPTH Compare
0  50030       36 @ 3159 W/270, LWD[GR,RES,PWD] @ 4015  3159     Yes
1  50030       36 @ 3159 W/270, LWD[GR,RES,PWD] @ 4015  3994      No
2  50030       36 @ 3159 W/270, LWD[GR,RES,PWD] @ 4015  5401      No
3  50030  26 @ 3994, LWD[GR,RES,PWD] @ 5430, 20 @ 5401  3159      No
4  50030  26 @ 3994, LWD[GR,RES,PWD] @ 5430, 20 @ 5401  3994     Yes
5  50030  26 @ 3994, LWD[GR,RES,PWD] @ 5430, 20 @ 5401  5401     Yes

Pandas: Determine if a string in one column is a substring of a string in another column

Let us try with numpy defchararray which is vectorized

from numpy.core.defchararray import find
find(df['1'].values.astype(str),df['0'].values.astype(str))!=-1
Out[740]: array([False,  True,  True, False])

Check if a column contains data from another column in python pandas

split the name into substrings, and use a list comprehension with any to get True is any string matches:

df['result'] = [any(s in url for s in lst)
                for lst, url in zip(df['name'].str.split(), df['url'])]

the (slower) equivalent with apply would be:

df['result'] = df.apply(lambda x: any(s in x['url']
                        for s in x['name'].split()), axis=1)

output:

       name                url  result
0  pau lola    www.paulola.com    True
1  pou gine  www.cheeseham.com   False
2  pete raj    www.pataraj.com    True

Pandas dataframe: Check if regex contained in a column matches a string in another column in the same row

You can't use a pandas builtin method directly. You will need to apply a re.search per row:

import re

mask = df.apply(lambda r: bool(re.search(r['patterns'], r['strings'])), axis=1)
df2 = df[mask]

or using a (faster) list comprehension:

mask = [bool(re.search(p,s)) for p,s in zip(df['patterns'], df['strings'])]

output:

  strings patterns group
0   apple      \ba     1
3   train      n\b     2
4     tan      n\b     2

Check if string in one column is contained in string of another column in the same row and add new column with matching column name

>>> df
  to_find col1 col2
0       a   ab   ac
1       b   aa   ba
2       c   bc   ee
>>> df['found_in'] = df.apply(lambda x: ' '.join(x.iloc[1:][x.iloc[1:].str.contains(str(x['to_find']))].index), axis=1)
>>> df
  to_find col1 col2   found_in
0       a   ab   ac  col1 col2
1       b   aa   ba       col2
2       c   bc   ee       col1

For better readability,

>>> def get_columns(x):
...     y = x.iloc[1:]
...     return y.index[y.str.contains(str(x['to_find']))]
... 
>>> df['found_in'] = df.apply(lambda x: ' '.join(get_columns(x)), axis=1)

Returning yes in one column if it contains a string in another column

MaterialsTracking_df['Valid Site'] = "Y" if ...

assigns a value to all rows.

Use pandas.DataFrame.apply instead
https://pandas.pydata.org/pandas-docs/version/0.24.2/reference/api/pandas.DataFrame.apply.html

example (I added another dummy row where the condition doesn't meet):

import pandas as pd
from io import StringIO

Materials_Tracking_df = pd.read_csv(StringIO("""
EXAM;Scoring Site DBN;Exams for this Site
MXRC;04M435;MXRC, MXRK, MXRN
MXRC;04M435;MXRC, MXRK, MXRN
SXRK;03M076;SXRK, SXRU
MXRC;04M435;MXRC, MXRK, MXRN
SXRK;04____;MXRC, MXRK, MXRN
"""), sep=';')

Materials_Tracking_df['Valid Site'] = Materials_Tracking_df.apply(
    lambda r: 'T' if r['EXAM'] in r['Exams for this Site'] else 'N'
, axis=1)

---

   EXAM Scoring Site DBN Exams for this Site Valid Site
0  MXRC           04M435    MXRC, MXRK, MXRN          T
1  MXRC           04M435    MXRC, MXRK, MXRN          T
2  SXRK           03M076          SXRK, SXRU          T
3  MXRC           04M435    MXRC, MXRK, MXRN          T
4  SXRK           04____    MXRC, MXRK, MXRN          N

python pandas - Check if partial string in column exists in other column

This looks like an expensive operation. You can try:

df['col2'].apply(lambda x: 'Yes' if df['col1'].str.contains(x).any() else 'No')

Output:

0     No
1    Yes
2    Yes
Name: col2, dtype: object

Most efficient way of checking whether a string is present in another column's values in Pandas

Try using issubset() with str.split():

df["check1_output"] = df.apply(lambda x: set(x["items_check1"].split(",")).issubset(x["all_items"].split(",")), axis=1)
df["check2_output"] = df.apply(lambda x: set(x["items_check2"].split(",")).issubset(x["all_items"].split(",")), axis=1)
>>> df
     id              all_items  ... check1_output check2_output
0  1239  foobar,foo,foofoo,bar  ...          True          True
1  3298             foobar,foo  ...          True         False
2  9384                foo,bar  ...         False          True

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