如何在 Pandas DataFrame 中找到第一个唯一元素的索引？

Question

考虑

df1 = pd.DataFrame("Name":["Adam","Joseph","James","James","Kevin","Kevin","Kevin","Peter","Peter"])

我想获取 dataframe 中唯一值的索引。

当我做df1["Name"].unique()我得到 output 为

['Adam','Joseph','James','Kevin','Peter']

但我想获取每个值第一次出现的位置

[0,1,2,4,7]

Answer 1

我建议使用numpy.unique并将return_index设为 True。

np.unique(df1, return_index=True)
Out[13]: 
(array(['Adam', 'James', 'Joseph', 'Kevin', 'Peter'], dtype=object),
 array([0, 2, 1, 4, 7], dtype=int64))

Answer 2

numpy 答案很好，但这是一种解决方法：

out = df1.reset_index().groupby(['Name'])['index'].min().to_list()

output：

[0, 1, 2, 4, 7]

Answer 3

使用RANK检查下面的代码

df1['rank'] = df1.groupby(['Name'])['Name'].rank(method='first')
df1[df1['rank'] == 1].index

Int64Index([0, 1, 2, 4, 7], dtype='int64')

Answer 4

第一场比赛=第一个位置

In[49]: import pandas as pd
   ...: df1 = pd.DataFrame({"Name":["Adam","Joseph","James","James","Kevin","Kevin","Kevin","Peter","Peter"]})
   ...: print ([df1.loc[df1['Name']==i].index[0] for i in df1['Name'].unique()])
   ...: 
[0, 1, 2, 4, 7]