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I'm not sure where I am astray but I cannot seem to reset the index on a dataframe.
When I run test.head(), I get the output below:
As you can see, the dataframe is a slice, so the index is out of bounds.
What I'd like to do is to reset the index for this dataframe. So I run test.reset_index(drop=True). This outputs the following:
That looks like a new index, but it's not. Running test.head again, the index is still the same. Attempting to use lambda.apply or iterrows() creates problems with the dataframe.
How can I really reset the index?
756
pandas. reset_index in pandas is used to reset index of the dataframe object to default indexing (0 to number of rows minus 1) or to reset multi level index. By doing so, the original index gets converted to a column.
Use DataFrame.reset_index() function We can use DataFrame. reset_index() to reset the index of the updated DataFrame. By default, it adds the current row index as a new column called 'index' in DataFrame, and it will create a new row index as a range of numbers starting at 0.
repeat() function repeat elements of an Index. The function returns a new index where each element of the current index is repeated consecutively a given number of times.
reset_index by default does not modify the DataFrame; it returns a new DataFrame with the reset index. If you want to modify the original, use the inplace argument: df.reset_index(drop=True, inplace=True). Alternatively, assign the result of reset_index by doing df = df.reset_index(drop=True).
115
BrenBarn's answer works.
The following also worked via this thread, which isn't a troubleshooting so much as an articulation of how to reset the index:
test = test.reset_index(drop=True)
As an extension of in code veritas's answer... instead of doing del at the end:
test = test.reset_index()
del test['index']
You can set drop to True.
test = test.reset_index(drop=True)
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