从 python 中的日期开始对月份和日期进行分组

Question

我有这样的数据框

  Date        Temerature
2016-01-01      3
2017-01-01      4
2016-02-01      5
2017-02-01      7
2016-03-01      2
2017-03-01      4

现在，我想像这样获取基于月份和日期的平均温度温度

 Date      Temperature
Jan 1         3.5
Feb 1         6
Mar 1         3

所以，我想制作一个像这样的新数据框，在 python 中如何实现？

Answer 1

尝试：

df['Date'] = pd.to_datetime(df['Date'])
df.groupby(df['Date'].dt.strftime('%B %d'), sort=False).mean()

输出：

             Temerature
Date                   
January 01          3.5
February 01         6.0
March 01            3.0

Answer 2

试试这个：

import pandas as pd

df = pd.DataFrame({'Date': ['2016-01-01', '2017-01-01', '2016-02-01', '2017-02-01', '2016-03-01', '2017-03-01'],
                   'Temerature': [3, 4, 5, 7, 2, 4]})

df['Date'] = pd.to_datetime(df['Date'])
df['Month'] = df['Date'].dt.month
df['Day'] = df['Date'].dt.day

df.groupby(['Month', 'Day'])['Temerature'].mean().reset_index()

Answer 3

你的table：

import pandas as pd

df = pd.DataFrame({
    "Date":["2016-01-01","2017-01-01","2016-02-01","2017-02-01","2016-03-01 ","2017-03-01 "],
    "Temerature":[3,4,5,7,2,4]
})

转换数据：

df["Date"] = pd.to_datetime(df["Date"], infer_datetime_format=True)
df["Date"] = df["Date"].dt.strftime('%B %d')

df = df.groupby(["Date"], sort=False).mean().reset_index()

输出：

print(df)  
          Date  Temerature
0   January 01         3.5
1  February 01         6.0
2     March 01         3.0

从 python 中的日期开始对月份和日期进行分组

Grouping Month and day from the Date in python

python

datetime

data-analysis

dataframe

pandas