根据Python Pandas中另一个数据框中的数据选择一个数据框中的行

Question

I have two dataframes created with Pandas. The first one has co-occurrences of items happening in certain years:

   Date Item1 Item2
0  1975     a     b
1  1976     b     c
2  1977     b     a
3  1977     a     b
4  1978     c     d
5  1979     e     f
6  1980     a     f

The second one has birthdates of the items:

Birthdate Item    
1975     a
1975     b
1976     c
1978     d
1979     f
1979     e

Now, I want to set an age variable, for example:

age = 2 

And then populate a third dataframe (alternative transform the first one) so that I get a version of the first one keeping only rows of co-occurrences that happened when Item1 was below the defined 'age'.

Answer 1

You could merge DataFrames - it is similar to join in SQL

import pandas

data = [
    [1975,'a','b'],
    [1976,'b','c'],
    [1977,'b','a'],
    [1977,'a','b'],
    [1978,'c','d'],
    [1979,'e','f'],
    [1980,'a','f'],
]

birthdate = [
    [1975,'a'],
    [1975,'b'],
    [1976,'c'],
    [1978,'d'],
    [1979,'f'],
    [1979,'e']
]

df1 = pandas.DataFrame(data, columns = ['Date', 'Item1', 'Item2'])
df2 = pandas.DataFrame(birthdate, columns = ['Birthdate', 'Item'])

#print df1
#print df2

newdf = pandas.merge(left=df1, right=df2, left_on='Item1', right_on='Item')

print newdf

print newdf[ newdf['Birthdate'] > 1975 ]

.

   Date Item1 Item2  Birthdate Item
0  1975     a     b       1975    a
1  1977     a     b       1975    a
2  1980     a     f       1975    a
3  1976     b     c       1975    b
4  1977     b     a       1975    b
5  1978     c     d       1976    c
6  1979     e     f       1979    e

   Date Item1 Item2  Birthdate Item
5  1978     c     d       1976    c
6  1979     e     f       1979    e