jea*_*elj 4 python indexing datetime pandas
我有按日期的数据,并希望按周创建一个新的数据框,其中包括销售额和类别数量.
#standard packages
import numpy as np
import pandas as pd
#visualization
%matplotlib inline
import matplotlib.pylab as plt
#create weekly datetime index
edf = pd.read_csv('C:\Users\j~\raw.csv', parse_dates=[6])
edf2 = edf[['DATESENT','Sales','Category']].copy()
edf2
#output
DATESENT | SALES | CATEGORY
2014-01-04 100 A
2014-01-05 150 B
2014-01-07 150 C
2014-01-10 175 D
#create datetime index of week
edf2['DATESENT']=pd.to_datetime(edf2['DATESENT'],format='%m/%d/%Y')
edf2 = edf2.set_index(pd.DatetimeIndex(edf2['DATESENT']))
edf2.resample('w').sum()
edf2
#output
SALES CATEGORY
DATESENT
2014-01-05 250 AB
2014-01-12 325 CD
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但我在寻找
SALES CATEGORY
DATESENT
2014-01-05 250 2
2014-01-12 325 2
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这不起作用......
edf2 = e2.resample('W').agg("Category":len,"Sales":np.sum)
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谢谢
Sco*_*ton 10
Agg将字典作为各种格式的参数.
edf2 = e2.resample('W').agg({"Category":'size',"Sales":'sum'})
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