从熊猫-Python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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