3 回答

TA貢獻(xiàn)1856條經(jīng)驗(yàn) 獲得超17個(gè)贊
這是你想要的嗎?
df = df.set_index('id')
dictionary = {1:[5,8,6,3], 2:[1,2], 5:[8,6,2]}
df['new_column'] = pd.Series(dictionary)
注意:字典的鍵需要與數(shù)據(jù)框的索引具有相同的類型(int)。
>>> print(df)
gender new_column
id
1 0 [5, 8, 6, 3]
2 0 [1, 2]
3 1 NaN
4 1 NaN
5 1 [8, 6, 2]
更新:
如果列包含重復(fù)項(xiàng),則更好的解決方案'id'(請(qǐng)參閱下面的評(píng)論):
df['new_column'] = df['id'].map(dictionary)

TA貢獻(xiàn)1789條經(jīng)驗(yàn) 獲得超10個(gè)贊
import pandas as pd
df = pd.DataFrame({'id':[1,2,3,4,5], 'gender':[0,0,1,1,1]})
dictionary = {'1':[5,8,6,3], '2':[1,2], '5':[8,6,2]}
然后只需創(chuàng)建一個(gè)包含您想要的值的列表并將它們添加到您的數(shù)據(jù)框中
newValues = [ dictionary.get(str(val),[]) for val in df['id'].values]
df['new_column'] = newValues
>>> print(df)
gender new_column
id
1 0 [5, 8, 6, 3]
2 0 [1, 2]
3 1 []
4 1 []
5 1 [8, 6, 2]

TA貢獻(xiàn)1946條經(jīng)驗(yàn) 獲得超4個(gè)贊
[]您可以使用默認(rèn)具有值的特殊字典來構(gòu)造您的列。
from collections import defaultdict
default_dictionary = defaultdict(list)
id = [1,2,3,4,5]
dictionary = {'1':[5,8,6,3], '2':[1,2], '5':[8,6,2]}
for n in dictionary:
default_dictionary[n] = dictionary[n]
new_column = [default_dictionary[str(n)] for n in id]
new_column 是[[5, 8, 6, 3], [1, 2], [], [], [8, 6, 2]]現(xiàn)在,你可以把它傳遞給你的最后一個(gè)論點(diǎn)pd.DataFrame(...)
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