如何在Python中按天汇总时间序列数据？ resample.sum（）无效 [英] How do I sum time series data by day in Python? resample.sum() has no effect

问题描述

我是Python的新手。如何根据日期对数据求和并绘制结果？

我有一个Series对象，其数据如下：

  2017-11-03 07:30:00 NaN 
 2017-11-03 09:18:00 NaN 
 2017-11-03 10:00： 00 NaN 
 2017-11-03 11:08:00 NaN 
 2017-11-03 14:39:00 NaN 
 2017-11-03 14:53:00 NaN 
 2017-11-03 15:00:00 NaN 
 2017-11-03 16:00:00 NaN 
 2017-11-03 17:03:00 NaN 
 2017-11- 03 17:42:00 800.0 
 2017-11-04 07:27:00 600.0 
 2017-11-04 10:10:00 NaN 
 2017-11-04 11:48： 00 NaN 
 2017-11-04 12:58:00 500.0 
 2017-11-04 13:40:00 NaN 
 2017-11-04 15:15:00 NaN 
 2017-11-04 16:21:00 NaN 
 2017-11-04 17:37:00 500.0 
 2017-11-04 21:37:00 NaN 
 2017-11-04 05 03:00:00 NaN 
 2017-11-05 06:30:00 NaN 
 2017-11-05 07:19:00 NaN 
 2017-11-05 08:31： 00 200.0 
 2017-11-05 09:31:00 500.0 
 2017-11-05 12:03:00 NaN 
 2017-11-05 12 ：25：00 200.0 
 2017-11-05 13:11:00 500.0 
 2017-11-05 16:31:00 NaN 
 2017-11-05 19:00:00 500.0 
 2017-11-06 08:08:00 NaN 
  

我有以下代码：

 ＃加载程序包
导入熊猫为pd 
导入matplotlib.pyplot为plt 
 
＃导入止痛药数据
 df = pd.read_csv（'/ Users / user / Documents / health / PainOverTime.csv'，delimiter ='，'）
 
＃绘图条形图日期和止痛药用量
次= pd.to_datetime（df.loc [：，'Time']）
 
 ts = pd.Series（df.loc [：，'acetaminophen'] .values，index = times，
 name ='Painkiller over time'）
 ts.plot（）
  

这给了我以下线图（？）图：

这是一个开始；现在我想按日期对剂量求和。但是，此代码无法实现任何更改：结果图相同。怎么了？

  ts.resample（'D'，closed ='left'，label ='right'）。sum （）
 ts.plot（）
  

我也尝试过 ts.resample（'D'）。sum（）， ts.resample（'1d'）。sum（）， ts.resample（'1D'）。sum（），但是图中没有变化。

.resample 甚至是正确的功能吗？我了解从数据中重新采样是采样，例如

也就是说，我希望获得一些结果（基于上述数据），例如：

  2017-11-03 800 
 2017-11-04 1600 
 2017-11-05 1900 
 2017-11-06 NaN 
  

解决方案

此方法是否不优于'groupby'函数？

现在我该如何制作散点图或条形图呢？线图...？

I am new to Python. How do I sum data based on date and plot the result?

I have a Series object with data like:

2017-11-03 07:30:00      NaN
2017-11-03 09:18:00      NaN
2017-11-03 10:00:00      NaN
2017-11-03 11:08:00      NaN
2017-11-03 14:39:00      NaN
2017-11-03 14:53:00      NaN
2017-11-03 15:00:00      NaN
2017-11-03 16:00:00      NaN
2017-11-03 17:03:00      NaN
2017-11-03 17:42:00    800.0
2017-11-04 07:27:00    600.0
2017-11-04 10:10:00      NaN
2017-11-04 11:48:00      NaN
2017-11-04 12:58:00    500.0
2017-11-04 13:40:00      NaN
2017-11-04 15:15:00      NaN
2017-11-04 16:21:00      NaN
2017-11-04 17:37:00    500.0
2017-11-04 21:37:00      NaN
2017-11-05 03:00:00      NaN
2017-11-05 06:30:00      NaN
2017-11-05 07:19:00      NaN
2017-11-05 08:31:00    200.0
2017-11-05 09:31:00    500.0
2017-11-05 12:03:00      NaN
2017-11-05 12:25:00    200.0
2017-11-05 13:11:00    500.0
2017-11-05 16:31:00      NaN
2017-11-05 19:00:00    500.0
2017-11-06 08:08:00      NaN

I have the following code:

# load packages
import pandas as pd
import matplotlib.pyplot as plt

# import painkiller data
df = pd.read_csv('/Users/user/Documents/health/PainOverTime.csv',delimiter=',')

# plot bar graph of date and painkiller amount
times = pd.to_datetime(df.loc[:,'Time'])

ts = pd.Series(df.loc[:,'acetaminophen'].values, index = times,
               name = 'Painkiller over Time')
ts.plot()

This gives me the following line(?) graph:

It's a start; now I want to sum the doses by date. However, this code fails to effect any change: The resulting plot is the same. What is wrong?

ts.resample('D',closed='left', label='right').sum()
ts.plot()

I have also tried ts.resample('D').sum(), ts.resample('1d').sum(), ts.resample('1D').sum(), but there is no change in the plot.

Is .resample even the correct function? I understand resampling to be sampling from the data, e.g. randomly taking one point per day, whereas I want to sum each day's values.

Namely, I'm hoping for some result (based on the above data) like:

2017-11-03 800
2017-11-04 1600
2017-11-05 1900
2017-11-06 NaN

解决方案

This answer helped me see that I needed to assign it to a new object (if that's the right terminology):

import pandas as pd
import matplotlib.pyplot as plt
df = pd.read_csv('/Users/user/Documents/health/PainOverTime.csv',delimiter=',')
# plot bar graph of date and painkiller amount
times = pd.to_datetime(df.loc[:,'Time'])

# raw plot of data
ts = pd.Series(df.loc[:,'acetaminophen'].values, index = times,
               name = 'Painkiller over Time')
fig1 = ts.plot()

# combine data by day
test2 = ts.resample('D').sum()
fig2 = test2.plot()

That produces the following plots:

Is this method not better than the 'groupby' function?

Now how do I make a scatter or bar plot instead of this line plot...?

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