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I'm trying to drop pandas dataframe row based on its index (not location).
The data frame looks like
DO 129518 a developer and 20066 responsible for 571 responsible for 85629 responsible for 5956 by helping them (FYI: "DO" is a column name)
I want to delete the row where its index is 571 so I did:
df=df.drop(df.index[571]) then I check df.ix[571]
then what the hell it's still there!
So I thought "ok, maybe index and ix are different!"
In [539]: df.index[571] 17002 My question is
1) What is index? (compared to ix)
2) How do I delete the index row 571 using ix?
410
Use pandas. DataFrame. drop() method to delete/remove rows with condition(s).
Use iloc to get the row as a Series, then get the row's index as the 'name' attribute of the Series. Then use the index to drop.
Delete a Multiple Rows by Index Position in DataFrame As df. drop() function accepts only list of index label names only, so to delete the rows by position we need to create a list of index names from positions and then pass it to drop().
You should drop the desired value from the index directly:
df.drop(571, inplace=True) 
df.index Is the index of the dataframe.
df.index[571] Is the 571st element of the index. Then you dropped whatever that was. You didn't want positional but that's what you did.
Use @John Zwinck's answer
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