按非透视数据框列过滤透视表
[英]Filtering a pivot table by non pivot dataframe column
问题描述
I have a dataframe (df)
我有一个数据框（df）
id company sector currency price
0 BBG.MTAA.MS.S MEDIASET SPA Communications EUR 4.334000
1 BBG.MTAA.TIT.S TELECOM ITALIA SPA Communications EUR 1.091000
2 BBG.XETR.DTE.S DEUTSCHE TELEKOM AG-REG Communications EUR 15.460000
3 BBG.XLON.BARC.S BARCLAYS PLC Financial GBp 3.414498
4 BBG.XLON.BTA.S BT GROUP PLC Communications GBp 5.749122
5 BBG.XLON.HSBA.S HSBC HOLDINGS PLC Financial GBp 6.716041
6 BBG.XLON.LLOY.S LLOYDS BANKING GROUP PLC Financial GBp 1.027752
7 BBG.XLON.STAN.S STANDARD CHARTERED PLC Financial GBp 9.707300
8 BBG.XLON.TRIL.S THOMSON REUTERS UK LTD Communications GBp NaN
9 BBG.XLON.VOD.S VODAFONE GROUP PLC Communications GBp 3.035487
10 BBG.XMCE.BBVA.S BANCO BILBAO VIZCAYA ARGENTA Financial EUR 7.866000
I can create a pivot table on the sector field (to find out how many companies are in the same sector) using the following code:我可以使用以下代码在部门字段上创建数据透视表（以找出同一部门中有多少家公司）：
sectorPivot = df.pivot_table(index=['sector'], aggfunc='count')
Which looks like this:看起来像这样：
currency id company
sector
Communications 6 6 6
Financial 5 5 5
However I would like to filter out the companies with a price that is equal to 'NaN' so I have a pivot table that looks like但是我想过滤掉价格等于“NaN”的公司，所以我有一个看起来像的数据透视表
currency id company
sector
Communications 5 5 5
Financial 5 5 5
(Note that the count of the communications sector has decreased by 1 from 6 to 5 due to the 'NaN' price for one of the broad_sector stocks). （请注意，由于其中一只大板块股票的'NaN'价格，通信板块的数量从 6 减少了 1 到 5）。
How can I do this?我该怎么做？
1 个解决方案
解决方案1
1 2016-07-14 13:33:45
Use dropna(subset=['price'] ahead of your pivot.在您的枢轴之前使用dropna(subset=['price'] 。
df.dropna(subset=['price']).pivot_table(index=['sector'], aggfunc='count')
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