How can I reindex pandas dataframe to reset the starting index value to zero？ [duplicate]

Question

In my dataframe, there are NaN values in some rows. I want to delete these rows. I solve it with dataframe.dropna(how='any'). The result looks like:

         date  time   open   hign    low  close  volume  turnover
2  2015-09-01   931  48.60  48.60  48.00  48.00  449700  21741726
3  2015-09-01   932  47.91  48.33  47.91  48.25  158500   7614508

I want to reindex the rows of my dataframe, so I run:

length = dataframe.dropna(how='any').shape[0]
dataframe1 = dataframe.index(range(length))

But dataframe1 still keeps the old index values, like：

          date  time   open   hign    low  close  volume  turnover
0         NaN   NaN    NaN    NaN    NaN    NaN     NaN       NaN
1         NaN   NaN    NaN    NaN    NaN    NaN     NaN       NaN
2  2015-09-01   931  48.60  48.60  48.00  48.00  449700  21741726
3  2015-09-01   932  47.91  48.33  47.91  48.25  158500   7614508

How can I make the number begin with 0 and delete the first two rows?

Desired result:

          date  time   open   hign    low  close  volume  turnover
0  2015-09-01   931  48.60  48.60  48.00  48.00  449700  21741726
1  2015-09-01   932  47.91  48.33  47.91  48.25  158500   7614508

Alexander · Accepted Answer · 2015-12-09 04:12:47Z

7

Reset the index and specify drop=True.

df = pd.DataFrame({'close': [nan, nan, 48.0, 48.25],
                   'date': [nan, nan, '2015-09-01', '2015-09-01'],
                   'hign': [nan, nan, 48.60, 48.33],
                   'low': [nan, nan, 48.0, 47.91],
                   'open': [nan, nan, 48.60, 47.91],
                   'time': [nan, nan, 931.0, 932.0],
                   'turnover': [nan, nan, 21741726.0, 7614508.0],
                   'volume': [nan, nan, 449700.0, 158500.0]})

>>> df
         date  time   open   hign    low  close  volume  turnover
0         NaN   NaN    NaN    NaN    NaN    NaN     NaN       NaN
1         NaN   NaN    NaN    NaN    NaN    NaN     NaN       NaN
2  2015-09-01   931  48.60  48.60  48.00  48.00  449700  21741726
3  2015-09-01   932  47.91  48.33  47.91  48.25  158500   7614508

>>> df.dropna(how='any').reset_index(drop=True)
         date  time   open   hign    low  close  volume  turnover
0  2015-09-01   931  48.60  48.60  48.00  48.00  449700  21741726
1  2015-09-01   932  47.91  48.33  47.91  48.25  158500   7614508

edited Dec 9, 2015 at 4:12

answered Dec 9, 2015 at 4:05

Alexander

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1 Comment

Peng He Over a year ago

Thanks.That helps me a lot.

hd1 · Accepted Answer · 2015-12-09 03:34:08Z

-1

Did you try the reindex functionality?

answered Dec 9, 2015 at 3:34

hd1

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