pandas 如何更新熊猫中的现有数据框？
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how to update existing data frame in pandas?
提问by HappyPy
Given these two data frames:
鉴于这两个数据框：
>>> df1 = pd.DataFrame({'c1':['a','a','b','b'], 'c2':['x','y','x','y'], 'val':0})
>>> df1
c1 c2 val
0 a x 0
1 a y 0
2 b x 0
3 b y 0
>>> df2 = pd.DataFrame({'c1':['a','a','b'], 'c2':['x','y','y'], 'val':[12,31,14]})
>>> df2
c1 c2 val
0 a x 12
1 a y 31
2 b y 14
Is there a function that takes the elements of valfrom df2and puts them in the corresponding indexes of df1, resulting in:
是否有一个函数可以获取valfrom的元素df2并将它们放在 的相应索引中df1，从而导致：
>>> df1_updated
c1 c2 val
0 a x 12
1 a y 31
2 b x 0
3 b y 14
回答by elyase
Yes, take a look at combine_firstor update. For example:
是的，看看combine_first或update。例如：
>>> df1['val'] = df2['val'].combine_first(df1['val'])
>>> df1
Out[26]:
c1 c2 val
0 a x 12
1 a y 31
2 b x 14
3 b y 0
EDIT: to combine according to c1 and c2 ignoring the current index:
编辑：根据 c1 和 c2 组合忽略当前索引：
>>> df1['val'] = df2.set_index(['c1','c2'])['val'].combine_first(df1.set_index(['c1','c2'])['val']).values
>> df1
Out[25]:
c1 c2 val
0 a x 12
1 a y 31
2 b x 0
3 b y 14
