Shortest way to extract certain rows from DataFrame in Pandas

Asked Nov 24 '18 at 11:55

Active Nov 24 '18 at 11:57

Viewed 17 times

I need to extract certain rows from my dataset. The indeces of the rows I need are detected from another column in another variable. My dataframe is something like (with more columns)

1     data1
2     data2
3     data3
4     data4
5     data5

My other column is another variable and it's like

1     true
2     false
3     true
4     false
5     false

I put a boolean, moreover I need to check values in my column that satisfy a condition, I need those indeces and then I want to extract rows with those indeces from my dataset.

edited Nov 24 '18 at 11:57

asked Nov 24 '18 at 11:55

james watt

Use `df[df['boolean column']]` – jezrael Nov 24 '18 at 11:58
I already saw the loc method but can I use it passing another variable different from my df? – james watt Nov 24 '18 at 12:00
Solution aboce is like `df[df['boolean column'] == True]`, but if compare with strings then need `df[df['boolean column'] == 'true']`. `loc` here is not necessary – jezrael Nov 24 '18 at 12:01
I think you did not understand. I need to use another variable, something like `df1[df2['column name'] = 'something']`, but can I do this if `df2` is a serie? – james watt Nov 24 '18 at 12:06
OK, so change `something` to `True` or `true`, something missing ? – jezrael Nov 24 '18 at 12:08
If `Series` then use `df[s == 'something']` but necessary same index values in `df` and `s` – jezrael Nov 24 '18 at 12:10
1

Ok it works, I thought it was more difficult. Thanks. – james watt Nov 24 '18 at 12:21

Shortest way to extract certain rows from DataFrame in Pandas

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