问题描述
我有两个DataFrames. . .
I have two DataFrames . . .
df1是一个表，我需要从使用索引的值中提取值，这些索引是从df2中的多个列中检索到的.
df1 is a table I need to pull values from using index, column pairs retrieved from multiple columns in df2.
我看到有一个函数get_value在给定索引和列值时可以完美地工作，但是当尝试向量化此函数以创建新列时，我无法实现...
I see there is a function get_value which works perfectly when given an index and column value, but when trying to vectorize this function to create a new column I am failing...
df1 = pd.DataFrame(np.arange(20).reshape((4, 5)))
df1.columns = list('abcde')
df1.index = ['cat', 'dog', 'fish', 'bird']
a b c d e
cat 0 1 2 3 4
dog 5 6 7 8 9
fish 10 11 12 13 14
bird 15 16 17 18 19
df1.get_value('bird, 'c')
17
现在我需要做的是在df2上创建一个全新的列-当基于索引对df1进行索引时，df2中指定的animal，letter列中的列对可以有效地向量化上面的pd.get_value函数.
Now what I need to do is to create an entire new column on df2 -- when indexing df1 based on index, column pairs from the animal, letter columns specified in df2 effectively vectorizing the pd.get_value function above.
df2 = pd.DataFrame(np.arange(20).reshape((4, 5)))
df2['animal'] = ['cat', 'dog', 'fish', 'bird']
df2['letter'] = list('abcd')
0 1 2 3 4 animal letter
0 0 1 2 3 4 cat a
1 5 6 7 8 9 dog b
2 10 11 12 13 14 fish c
3 15 16 17 18 19 bird d
导致. . .
0 1 2 3 4 animal letter looked_up
0 0 1 2 3 4 cat a 0
1 5 6 7 8 9 dog b 6
2 10 11 12 13 14 fish c 12
3 15 16 17 18 19 bird d 18
推荐答案
有一个恰如其分地名为lookup的函数.
There's a function aptly named lookup that does exactly this.
df2['looked_up'] = df1.lookup(df2.animal, df2.letter)
df2
0 1 2 3 4 animal letter looked_up
0 0 1 2 3 4 cat a 0
1 5 6 7 8 9 dog b 6
2 10 11 12 13 14 fish c 12
3 15 16 17 18 19 bird d 18
这篇关于在 pandas 数据帧上的向量化查找的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！