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I want to locate a specific value which can occur in multiple columns . In my case it's "False" . I know how to search "False" in individual columns as

df.loc[df['column1']==False]
df.loc[df['column2']==False]

Is there a way to find all at once ?

Unnamed: 0  Incident ID CR Number   Victims Zip Code    Address Number  Latitude    Longitude   Year    Month   Day
0   False   False   True    True    True    True    True    True    True    True    True
1   False   True    False   False   True    True    True    True    True    True    True
2   True    True    True    True    True    True    False   True    True    True    True
3   True    True    False   True    True    True    True    True    True    True    True
4   True    True    True    True    True    True    True    True    False   True    True

I want to see their locations .Hopefully something like

df.applymap.loc(False)
Bhawani Rabisankar Sahoo
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  • "I want to see their locations". How do you want to see them, i.e., how exactly should the output look like? A list of row index/column name positions? A dataframe with "X" values where the occurrences are? Etc. – sander Sep 18 '22 at 19:01
  • `s = df.stack() ; s[~s]` (`s[s.eq(False)]` if you have values other than `True`/`False`) or if you want to assign: `df[~df] = 'X'` / `df[df.eq(False)] = 'X'` – mozway Sep 18 '22 at 19:10

1 Answers1

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If you want to get the indices stack, then slice:

s = df.stack()
s[s.eq(False)].index

Or if you only have True/False:

s[~s].index

In one line:

df.stack().loc[lambda s: ~s].index

If you want to assign value(s) on the False positions, a simple boolean indexing will do:

df[df.eq(False)] = 'X'`

# or, if only True/False in the df 
df[~df] = 'X'`
mozway
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