Python 熊猫月

我想在dataFrame中创建一个列，它将是另外两个数据帧的结果

在下面的示例中，创建了两个数据帧：df1和df2

然后创建了第三个数据帧，即前两个数据帧的连接点。在此df3中，“Dates”列已更改为dateTime类型

之后，创建了“DateMonth”列，其月份从“Dates”列中提取

在这个df3中，我需要一个新列，如果“DateMonth”列的月份出现在“months”列中，则该列的值为1

我的困难是在“月”列中，或者值为零，或者值是一个月列表

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如何实现此结果？

尝试以下解决方案：

import pandas as pd

# define function for df.apply
def matched(row):
    if type(row['months'])==str:
        # for the case ('Feb, Mar, Apr') - get numerical representation of month from your string and return True if the 'Dates' value matches with some list item
        return row['Dates'].month in [datetime.strptime(mon.strip(), '%b').month for mon in row['months'].split(',')]  
    else:
        # for numbers - return True if months match
        return row['Dates'].month==row['months']

# df1 and df2:
id_sales   = [1, 2, 3, 4, 5, 6]
col_names  = ['Id', 'parrotId', 'Dates']
df1        = pd.DataFrame(columns = col_names)
df1.Id     = id_sales
df1.parrotId = [1, 2, 3, 1, 2, 3]
df1.Dates  = ['2012-12-25', '2012-08-20', '2013-07-23', '2014-01-14', '2016-02-21', '2015-10-31']

col_names2 = ['parrotId', 'months']
df2        = pd.DataFrame(columns = col_names2)
df2.parrotId = [1, 2, 3]
df2.months = [12, ('Feb, Mar, Apr'), 0]

df3 = pd.merge(df1, df2, on = 'parrotId')
df3.Dates = pd.to_datetime(df3.Dates)

# use apply to run the function on each row, astype converts boolean to int (0/1) 
df3['DateMonth'] = df3.apply(matched, axis=1).astype(int)
df3

Output:      
Id  parrotId    Dates   months          DateMonth
0   1   1   2012-12-25  12              1
1   4   1   2014-01-14  12              0
2   2   2   2012-08-20  Feb, Mar, Apr   0
3   5   2   2016-02-21  Feb, Mar, Apr   1
4   3   3   2013-07-23  0               0
5   6   3   2015-10-31  0               0

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什么是鹦鹉？卢卡斯，首先，非常感谢你的帮助。不幸的是，它没有起作用。我收到一条错误消息：“未定义名称‘datetime’”。我甚至导入了datetime库，并在收到新的错误消息时再次运行了最后一步：“AttributeError:（'module'datetime'没有属性'strptime'，'发生在索引2'）“。第一次尝试时，我错误地导入了库。我以这种方式导入它，它工作得非常完美：从datetime导入datetime。再次感谢卢卡斯。卢卡斯，你对如何解决下面的错误有什么看法吗？ValueError:（‘未转换的数据仍然存在：t’，‘发生在索引16772’）@ngelo，我猜某个月的缩写中有一个拼写错误。当我这样做时：

df2.months=[12，（'Febt，Mar，Apr'），0]

，我会得到类似的错误（只是错误指数不同）。如果您从某个文件中读取源数据，请仔细查看并尝试查找不正确的月份缩写格式（可能有4个字符，以t结尾）。

import pandas as pd

# define function for df.apply
def matched(row):
    if type(row['months'])==str:
        # for the case ('Feb, Mar, Apr') - get numerical representation of month from your string and return True if the 'Dates' value matches with some list item
        return row['Dates'].month in [datetime.strptime(mon.strip(), '%b').month for mon in row['months'].split(',')]  
    else:
        # for numbers - return True if months match
        return row['Dates'].month==row['months']

# df1 and df2:
id_sales   = [1, 2, 3, 4, 5, 6]
col_names  = ['Id', 'parrotId', 'Dates']
df1        = pd.DataFrame(columns = col_names)
df1.Id     = id_sales
df1.parrotId = [1, 2, 3, 1, 2, 3]
df1.Dates  = ['2012-12-25', '2012-08-20', '2013-07-23', '2014-01-14', '2016-02-21', '2015-10-31']

col_names2 = ['parrotId', 'months']
df2        = pd.DataFrame(columns = col_names2)
df2.parrotId = [1, 2, 3]
df2.months = [12, ('Feb, Mar, Apr'), 0]

df3 = pd.merge(df1, df2, on = 'parrotId')
df3.Dates = pd.to_datetime(df3.Dates)

# use apply to run the function on each row, astype converts boolean to int (0/1) 
df3['DateMonth'] = df3.apply(matched, axis=1).astype(int)
df3

Output:      
Id  parrotId    Dates   months          DateMonth
0   1   1   2012-12-25  12              1
1   4   1   2014-01-14  12              0
2   2   2   2012-08-20  Feb, Mar, Apr   0
3   5   2   2016-02-21  Feb, Mar, Apr   1
4   3   3   2013-07-23  0               0
5   6   3   2015-10-31  0               0