import pandas as pd
from datetime import datetime
import numpy as np
# Generate dates
date_rng = pd.date_range(start='1/1/2023', end='1/08/2024', freq='D')
# Create Pandas dataframe
df = pd.DataFrame(date_rng, columns=['date'])
# Add column with random numbers as number as records we generated
df['data'] = np.random.randint(0,100,size=(len(date_rng)))
#display(df)
# Convert the data frame index to a datetime index
df['datetime'] = pd.to_datetime(df['date'])
df = df.set_index('datetime')
# delete\drop date column
df.drop(['date'], axis=1, inplace=True)
#df.head()
#=====================> Approach#1 <======================
# Manipulate index to convert yyyy-mm-dd to yyyy-mm format
df.index = df.index.strftime("%Y-%m")
#=====================> Approach#2 <======================
# Manipulate index to convert yyyy-mm-dd to yyyy-mm format
#df.index = pd.to_datetime(df.index).strftime('%Y-%m')
print(df)
3条答案
按热度按时间gblwokeq1#
使用
strftime
如下:7nbnzgx92#
你有两种可能:
如果索引包含日期作为字符串:
如果你的索引已经是
DatetimeIndex
,你可以这样做:示例:
如果你想处理一些日期操作,
PeriodIndex
更有用。要了解
strftime
的每个格式代码,请参阅文档oyt4ldly3#
输出:
参考文献: