pandas 如何重新索引熊猫数据帧以将起始索引值重置为零？
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How can I reindex pandas dataframe to reset the starting index value to zero？
提问by Peng He
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:
在我的数据框中，某些行中有 NaN 值。我想删除这些行。我用 dataframe.dropna(how='any') 解决了它。结果如下：
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:
我想重新索引我的数据帧的行，所以我运行：
length = dataframe.dropna(how='any').shape[0]
dataframe1 = dataframe.index(range(length))
But dataframe1 still keeps the old index values, like：
但是 dataframe1 仍然保留旧的索引值，例如：
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?
如何使数字以 0 开头并删除前两行？
Desired result:
想要的结果：
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
回答by Alexander
Reset the index and specify drop=True.
重置索引并指定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
