How to reset index in a pandas dataframe?
PythonIndexingPandasDataframePython Problem Overview
I have a dataframe from which I remove some rows. As a result, I get a dataframe in which index is something like that: [1,5,6,10,11] and I would like to reset it to [0,1,2,3,4]. How can I do it?
The following seems to work:
df = df.reset_index()
del df['index']
The following does not work:
df = df.reindex()
Python Solutions
Solution 1 - Python
DataFrame.reset_index is what you're looking for. If you don't want it saved as a column, then do:
df = df.reset_index(drop=True)
If you don't want to reassign:
df.reset_index(drop=True, inplace=True)
Solution 2 - Python
Another solutions are assign RangeIndex or range:
df.index = pd.RangeIndex(len(df.index))
df.index = range(len(df.index))
It is faster:
df = pd.DataFrame({'a':[8,7], 'c':[2,4]}, index=[7,8])
df = pd.concat([df]*10000)
print (df.head())
In [298]: %timeit df1 = df.reset_index(drop=True)
The slowest run took 7.26 times longer than the fastest. This could mean that an intermediate result is being cached.
10000 loops, best of 3: 105 µs per loop
In [299]: %timeit df.index = pd.RangeIndex(len(df.index))
The slowest run took 15.05 times longer than the fastest. This could mean that an intermediate result is being cached.
100000 loops, best of 3: 7.84 µs per loop
In [300]: %timeit df.index = range(len(df.index))
The slowest run took 7.10 times longer than the fastest. This could mean that an intermediate result is being cached.
100000 loops, best of 3: 14.2 µs per loop
Solution 3 - Python
data1.reset_index(inplace=True)