正在生成多个数据框和其他问题

Question

借用@DGS的解决方案，在数据框中使用基于YYMM的用户输入对行进行切片，在使用此代码时，我注意到了一些问题，

import pandas as pd

# Inputs
start_time = input('Start Period: ') # 1900 Jan or 1900
end_time = input('End Period: ') # 1910 May or 1910

# If month is present
if len(start_time.split()) > 1:
    start_year, start_month = start_time.split()
# no start month
else:
    start_year = start_time
    start_month = 'Jan'
# If end month
if len(end_time.split()) > 1:
    end_year, end_month = end_time.split()

#no end month
else:
    end_year = end_time
    end_month = 'Dec'

months = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']

df = pd.DataFrame(columns=['Year', 'Month']) # output dataframe

# Iterate between start and end year
for i in range(int(start_year), int(end_year)+1):
    temp_df = pd.DataFrame() #temporary dataframe
    if i == int(start_year):
        month_list = months[months.index(start_month):]
    elif i == int(end_year):
        month_list = months[:months.index(end_month)+1] if end_month != 'Dec' else months[:months.index(end_month)+1]
    else:
        month_list = months

    temp_df['Month'] = month_list
    temp_df['Year'] = i

    print(temp_df)

首先，当打印不同年份的用户输入时，会导致产生多个数据框，（只希望它是一个单独的数据框）

Start Period: 1990
End Period: 1992
   Month  Year
0    Jan  1990
1    Feb  1990
2    Mar  1990
3    Apr  1990
4    May  1990
5    Jun  1990
6    Jul  1990
7    Aug  1990
8    Sep  1990
9    Oct  1990
10   Nov  1990
11   Dec  1990
   Month  Year
0    Jan  1991
1    Feb  1991
2    Mar  1991
3    Apr  1991
4    May  1991
5    Jun  1991
6    Jul  1991
7    Aug  1991
8    Sep  1991
9    Oct  1991
10   Nov  1991
11   Dec  1991
   Month  Year
0    Jan  1992
1    Feb  1992
2    Mar  1992
3    Apr  1992
4    May  1992
5    Jun  1992
6    Jul  1992
7    Aug  1992
8    Sep  1992
9    Oct  1992
10   Nov  1992
11   Dec  1992

其次但并非最不重要的一点是，当打印同一年的用户输入时，会导致数据框始终在 12 月结束，（只是希望它在结束时间结束）

Start Period: 1990 Feb
End Period: 1990 Mar
   Month  Year
0    Feb  1990
1    Mar  1990
2    Apr  1990
3    May  1990
4    Jun  1990
5    Jul  1990
6    Aug  1990
7    Sep  1990
8    Oct  1990
9    Nov  1990
10   Dec  1990

Answer 1

因为您的循环仅适用于end_year > start_year ，因此对于这里的最小代码更改是在end_year == start_year时给出条件

df = pd.DataFrame(columns=['Year', 'Month']) # output dataframe

# Iterate between start and end year
if (start_year < end_year):
    for i in range(int(start_year), int(end_year) + 1):
        if i == int(start_year):
            month_list = months[months.index(start_month):]
        elif i == int(end_year):
            month_list = months[:months.index(end_month)+1]
        else:
            month_list = months

        df_temp = pd.DataFrame()
        df_temp['Month'] = month_list
        df_temp['Year'] = i

        df = df.append(df_temp, ignore_index=True)
elif (start_year == end_year):
        df_temp = pd.DataFrame()
        df_temp['Month'] = months[months.index(start_month):months.index(end_month)+1]
        df_temp['Year'] = start_year

        df = df.append(df_temp, ignore_index=True)
        
print(df)

结果：

start_time = '1910 Mar'
end_time = '1910 Jun'