从熊猫-蟒蛇的日期中提取周数

原文:https://www.geesforgeks.org/extract-week-number-from-date-in-pandas-python/

很多时候，当处理一些包含日期的数据时，我们可能需要从一个特定的日期中提取周数。在 Python 中，可以在熊猫的帮助下轻松完成。

例 1:

# importing pandas as pd
import pandas as pd 

# creating a dictionary containing a date
dict = {'Date':["2015-06-17"]}

# converting the dictionary to a dataframe
df = pd.DataFrame.from_dict(dict)

# converting the date to the required format
df['Date'] = pd.to_datetime(df['Date'], errors ='coerce')
df.astype('int64').dtypes

# extracting the week from the date
weekNumber = df['Date'].dt.week

print(weekNumber)

输出:

0    25
Name: Date, dtype: int64

示例 2: 我们也可以通过在‘Date’对象中添加更多的日期来对多个日期进行同样的操作。

# importing pandas as pd
import pandas as pd 

# creating a dictionary containing a date
dict = {'Date':["2020-06-17", "2020-01-14", 
                "2020-09-20", "2020-08-15"]}

# converting the dictionary to a 
# dataframe
df = pd.DataFrame.from_dict(dict)

# converting the date to the required 
# format
df['Date'] = pd.to_datetime(df['Date'],
                            errors ='coerce')
df.astype('int64').dtypes

# extracting the week from the date
weekNumber = df['Date'].dt.week

print(weekNumber)

输出:

示例 3: 使用 date_range() 和 to_series() 从多个日期的日期中提取周数。

• pandas.data_range(): It generates all the dates from the start to end date

  语法:

  pandas.date_range(开始、结束、句点、freq、tz、normalize、name、closed)

• pandas.to_series(): It creates a Series with both index and values equal to the index keys.

  语法:

  py Index.to_series(self, index, name)

# importing pandas as pd
import pandas as pd 

# generating all dates in given range
# with increment by days
allDates = pd.date_range('2020-06-27', '2020-08-03', freq ='W')

# converting dates to series
series = allDates.to_series()

series.dt.week

输出:

例 4: 在本例中，我们将使用熊猫。Series() 生成日期，并使用不同的方式将该系列转换为数据框。

熊猫。Series(): 用于创建带有轴标签的一维数组。 语法:

pandas.Series(data, index, dtype, name, copy, fastpath)

# importing pandas as pd
import pandas as pd 

# generating the series
dates = pd.Series(pd.date_range('2020-2-10',
                                periods = 5,
                                freq ='M'))

# converting to dataframe
df = pd.DataFrame({'date_given': dates})

# extracting the week number
df['week_number'] = df['date_given'].dt.week

df

输出:

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