Question

我有两个数据框：

df = pd.DataFrame({'America':["Ohio","Utah","New York"],
                   'Italy':["Rome","Milan","Venice"],
                   'Germany':["Berlin","Munich","Jena"]});


df2 = pd.DataFrame({'Cities':["Rome", "New York", "Munich"],
                   'Country':["na","na","na"]})

我想在df2“城市”列上进行查找，以找到我（df）上的城市，并将城市所在的国家/地区（df列名称）附加到df2国家/地区列中

Answer 1

按字典将melt与map一起使用：

df1 = df.melt()
print (df1)
  variable     value
0  America      Ohio
1  America      Utah
2  America  New York
3    Italy      Rome
4    Italy     Milan
5    Italy    Venice
6  Germany    Berlin
7  Germany    Munich
8  Germany      Jena

df2['Country'] = df2['Cities'].map(dict(zip(df1['value'], df1['variable'])))
#alternative, thanks @Sandeep Kadapa 
#df2['Country'] = df2['Cities'].map(df1.set_index('value')['variable'])
print (df2)
     Cities  Country
0      Rome    Italy
1  New York  America
2    Munich  Germany

Answer 2

在熔化并重命名第一个数据帧之后：

df1 = df.melt().rename(columns={'variable': 'Country', 'value': 'Cities'})

解决方案是简单的合并：

df2 = df2[['Cities']].merge(df1, on='Cities')

熊猫遍历行并找到列名

2 个答案: