Pandas 数据框每天重新采样和计数事件

Question

I have a dataframe with time-index. I can resample the data to get (eg) mean per-day, however I would like also to get the counts per day. Here is a sample:

import datetime
import pandas as pd
import numpy as np

dates = pd.date_range(datetime.datetime(2012, 4, 5, 11, 
0),datetime.datetime(2012, 4, 7, 7, 0),freq='5H')

var1 = np.random.sample(dates.size) * 10.0
var2 = np.random.sample(dates.size) * 10.0
df = pd.DataFrame(data={'var1': var1, 'var2': var2}, index=dates)

df1=df.resample('D').mean() 

I'd like to get also a 3rd column 'count' which counts per day:

count
3
5
7

Thank you very much!

Answer 1

Use Resampler.agg and then flatten MultiIndex in columns:

df1 = df.resample('D').agg({'var1': 'mean','var2': ['mean', 'size']}) 
df1.columns = df1.columns.map('_'.join)
df1 = df1.rename(columns={'var2_size':'count'})
print (df1)
            var1_mean  var2_mean  count
2012-04-05   3.992166   4.968410      3
2012-04-06   6.843105   6.193568      5
2012-04-07   4.568436   3.135089      1

Alternative solution with Grouper :

df1 = df.groupby(pd.Grouper(freq='D')).agg({'var1': 'mean','var2': ['mean', 'size']}) 
df1.columns = df1.columns.map('_'.join)
df1 = df1.rename(columns={'var2_size':'count'})
print (df1)
            var1_mean  var2_mean  count
2012-04-05   3.992166   4.968410      3
2012-04-06   6.843105   6.193568      5
2012-04-07   4.568436   3.135089      1

EDIT:

r = df.resample('D')
df1 = r.mean().add_suffix('_mean').join(r.size().rename('count'))
print (df1)
            var1_mean  var2_mean  count
2012-04-05   7.840487   6.885030      3
2012-04-06   4.762477   5.091455      5
2012-04-07   2.702414   6.046200      1