答案 0 :(得分:2)
考虑到您可以使df
如下所示:(只需除去上面写着Type A
的第一行)
GDP per capita 1950 1951 1952 1953
0 Antigua and Barbuda 3544 3633 3723 3817
1 Argentina 7540 7612 7019 7198
2 Armenia 1862 1834 1914 1958
3 Aruba 3897 3994 4094 4196
4 Australia 12073 12229 12084 12228
5 Austria 6919 7382 7386 7692
>>pd.melt(df,id_vars='GDP per capita',var_name='Year',value_name='GDP Value')
GDP per capita Year GDP Value
0 Antigua and Barbuda 1950 3544
1 Argentina 1950 7540
2 Armenia 1950 1862
3 Aruba 1950 3897
4 Australia 1950 12073
5 Austria 1950 6919
6 Antigua and Barbuda 1951 3633
7 Argentina 1951 7612
8 Armenia 1951 1834
9 Aruba 1951 3994
10 Australia 1951 12229
11 Austria 1951 7382
12 Antigua and Barbuda 1952 3723
13 Argentina 1952 7019
14 Armenia 1952 1914
15 Aruba 1952 4094
16 Australia 1952 12084
17 Austria 1952 7386
18 Antigua and Barbuda 1953 3817
19 Argentina 1953 7198
20 Armenia 1953 1958
21 Aruba 1953 4196
22 Australia 1953 12228
23 Austria 1953 7692
要获得与您发布的图片完全相同的外观,请使用:
df1=pd.melt(df,id_vars='GDP per capita',var_name='Year',value_name='GDP Value')
df1.rename(columns={'GDP per capita':'Country'},inplace=True)
df1['GDP'] = 'GDP per capita'
df1 = df1[['GDP','Country','Year','GDP Value']]
df1.to_csv('filepath+filename.csv,index=False)