【发布时间】：2016-10-01 18:51:48
【问题描述】：
我有一个 pandas，我的 groupby 操作将索引变成了糊状。我需要日期作为索引，在每个股票代码组中排序
为了说明。像这样设置熊猫：
import pandas as pd
from StringIO import StringIO
text = """Date Ticker Open High Low Adj_Close Volume
2015-04-09 vws.co 315.000000 316.100000 312.500000 311.520000 1686800
2015-04-10 vws.co 317.000000 319.700000 316.400000 312.700000 1396500
2015-04-13 vws.co 317.900000 321.500000 315.200000 315.850000 1564500
2015-04-14 vws.co 320.000000 322.400000 318.700000 314.870000 1370600
2015-04-15 vws.co 320.000000 321.500000 319.200000 316.150000 945000
2015-04-16 vws.co 319.000000 320.200000 310.400000 307.870000 2236100
2015-04-17 vws.co 309.900000 310.000000 302.500000 299.100000 2711900
2015-04-20 vws.co 303.000000 312.000000 303.000000 306.490000 1629700
2016-03-31 mmm 166.750000 167.500000 166.500000 166.630005 1762800
2016-04-01 mmm 165.630005 167.740005 164.789993 167.529999 1993700
2016-04-04 mmm 167.110001 167.490005 165.919998 166.399994 2022800
2016-04-05 mmm 165.179993 166.550003 164.649994 165.809998 1610300
2016-04-06 mmm 165.339996 167.080002 164.839996 166.809998 2092200
2016-04-07 mmm 165.880005 167.229996 165.250000 167.160004 2721900"""
df = pd.read_csv(StringIO(text), delim_whitespace=1, parse_dates=[0], index_col=0)
还有代码
import pandas as pd
from pandas.io.data import DataReader
import numpy as np
import time
import os
stocklist = ['vws.co','nflx','mmm']
print ('df.tail (Input df)\n',df.tail(6),'\n')
def Screener(group):
def diff_calc(group):
df['Difference'] = df['Adj_Close'].diff()
return df['Difference']
df['Difference'] = diff_calc(group)
return df
if __name__ == '__main__':
df = GetStock(stocklist, start, end)
df['Adj_Close'] = df['Adj Close']
for ticker in stocklist:
### groupby screeener (filtering to only rel ticker group)
df = df.groupby('Ticker', as_index=False).Adj_Close.apply(Screener)
df.reset_index().sort(['Ticker', 'Date'], ascending=[1,1]).set_index('Ticker')
print ('(Output df)\n',df,'\n')
# Test the first 7 rows of each group for rolling_mean transgress groups...
df_test = df.groupby('Ticker').head(7).reset_index().set_index('Date')
print ('df_test (summary from df) (Output)\n',df_test,'\n')
显然我的索引现在搞砸了，我不知道这是怎么发生的。
(Output df)
Ticker Open High Low Adj Close Adj_Close Date
0 0 0 2016-05-20 vws.co 443.00 446.30 441.40 442.90 442.90
2016-05-23 vws.co 442.00 446.70 439.90 439.90 439.90
2016-05-24 vws.co 439.10 450.00 438.10 450.00 450.00
2016-05-25 vws.co 455.50 466.10 454.30 464.90 464.90
2016-05-26 vws.co 465.00 470.80 464.60 464.60 464.60
2016-05-27 vws.co 464.00 480.70 461.20 476.00 476.00
2016-05-30 vws.co 477.00 481.80 473.10 475.00 475.00
2016-05-31 vws.co 474.00 479.30 472.20 479.00 479.00
2016-06-01 vws.co 477.40 480.20 472.90 474.40 474.40
2016-05-20 nflx 90.08 93.28 89.98 92.49 92.49
2016-05-23 nflx 92.98 95.29 92.85 94.89 94.89
2016-05-24 nflx 95.98 99.14 95.75 97.89 97.89
2016-05-25 nflx 99.00 100.31 98.30 100.20 100.20
我需要日期作为索引，在每个股票代码组中排序
谁能帮忙？
【问题讨论】：
-
不清楚你在问什么。这就是你所追求的吗？
df['Difference'] = df.groupby('Ticker')['Adj_Close'].diff() -
我需要日期作为索引，在每个股票代码组中排序
-
输入中的日期是否排序？
-
是的，日期在 groupby 的输入中排序。
标签： python pandas indexing group-by