Pandas - 使用 datetimeindex 对数据框进行排序
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Pandas - Sorting a dataframe by using datetimeindex
提问by Jeril
The following is my dataframe which holds values from multiple Excel files. I wanted to do a time series analysis, so I made the index as datetimeindex. But my index is not arranged according to the date. The following is my dataframe:
以下是我的数据框，其中包含来自多个 Excel 文件的值。我想做一个时间序列分析，所以我将索引设为datetimeindex. 但是我的索引不是按日期排列的。以下是我的数据框：
Item Details Unit Op. Qty Price Op. Amt. Cl. Qty Price.1 Cl. Amt.
Month
2013-04-01 5 In 1 Pcs -56.0 172.78 -9675.58 -68.0 175.79 -11953.96
2013-04-01 Adaptor Pcs -17.0 9.00 -152.99 -17.0 9.00 -152.99
2013-04-01 Agro Tape Pcs -2.0 26.25 -52.50 -2.0 26.25 -52.50
...
2014-01-01 12" Angal Pcs -6.0 31.50 -189.00 -6.0 31.50 -189.00
2014-01-01 13 Mm Electrical Drill Check Set -1.0 247.50 -247.50 -1.0 247.50 -247.50
2014-01-01 14" Blad Pcs -5.0 157.49 -787.45 -5.0 157.49 -787.45
...
2013-09-01 Zinc Bolt 1/4 X 2"(box) Box -1.0 899.99 -899.99 -1.0 899.99 -899.99
2013-09-01 Zorik 88 32gram Pcs -1.0 45.00 -45.00 -1.0 45.00 -45.00
2013-09-01 Zorrik 311 Gram Pcs -1.0 270.01 -270.01 -1.0 270.01 -270.01
It is not sorted according to the date. I wanted to sort the index and its respective rows also. I googled it and found that there is a way to sort the datetimeindex and is as follows:
不按日期排序。我还想对索引及其各自的行进行排序。我google了一下，发现有一种方法可以对datetimeindex进行排序，如下所示：
all_data.index.sort_values()
DatetimeIndex(['2013-04-01', '2013-04-01', '2013-04-01', '2013-04-01',
'2013-04-01', '2013-04-01', '2013-04-01', '2013-04-01',
'2013-04-01', '2013-04-01',
...
'2014-02-01', '2014-02-01', '2014-02-01', '2014-02-01',
'2014-02-01', '2014-02-01', '2014-02-01', '2014-02-01',
'2014-02-01', '2014-02-01'],
dtype='datetime64[ns]', name=u'Month', length=71232, freq=None)
But it is sorting only the index, how can I sort the entire dataframeaccording to the sorted index? Kindly help.
但它只对索引进行排序，如何根据排序的索引对整个数据帧进行排序？请帮助。
