Reputation: 571
I have a dataframe with multiindex which I want to convert to date()
index.
Here is an example emulation of the type of dataframes I have:
i = pd.date_range('01-01-2016', '01-01-2020')
x = pd.DataFrame(index = i, data=np.random.randint(0, 10, len(i)))
x = x.groupby(by = [x.index.year, x.index.month]).sum()
print(x)
I tried to convert it to date index by this:
def to_date(ind):
return pd.to_datetime(str(ind[0]) + '/' + str(ind[1]), format="%Y/%m").date()
# flattening the multiindex to tuples to later reset the index
x.set_axis(x.index.to_flat_index(), axis=0, inplace = True)
x = x.rename(index = to_date)
x.set_axis(pd.DatetimeIndex(x.index), axis=0, inplace=True)
But it is very slow. I think the problem is in the pd.to_datetime(str(ind[0]) + '/' + str(ind[1]), format="%Y/%m").date()
line. Would greatly appreciate any ideas to make this faster.
Upvotes: 0
Views: 140
Reputation: 75130
You can just use:
x.index=pd.to_datetime([f"{a}-{b}" for a,b in x.index],format='%Y-%m')
print(x)
0
2016-01-01 162
2016-02-01 119
2016-03-01 148
2016-04-01 125
2016-05-01 132
2016-06-01 144
2016-07-01 157
2016-08-01 141
2016-09-01 138
2016-10-01 168
2016-11-01 140
2016-12-01 137
2017-01-01 113
2017-02-01 113
2017-03-01 155
..........
..........
......
Upvotes: 1