我有两个数据框,都由名为 month
的日期列索引。第一个 df1
有八行。我关心的列是 df['num_percent']
,它看起来像这样:
2015-02-01 0.071549
2015-03-01 0.070368
2015-04-01 0.069291
2015-05-01 0.068394
2015-06-01 0.067452
2015-07-01 0.066302
2015-08-01 0.065543
2015-09-01 0.064591
Name: num_percent, dtype: float64
第二个数据框有 100,000 行。我关心的列是 df2['total_quantity']
,它的示例如下所示:
2014-11-01 324199
2014-12-01 378443
2015-01-01 367379
2015-02-01 336863
2015-03-01 380268
2015-04-01 386292
2015-05-01 373213
2015-06-01 403343
2015-07-01 414310
2015-08-01 403684
2015-09-01 420922
Name: total_quantity, dtype: int64
我想向 df2
添加一个新列,它是 df2['total_quantity']
的值乘以 df1 中月份的相应值
。
我该怎么做?
如果我尝试:
df2['percent'] = df2['total_quantity'] * df1['num_percent']
我收到 ValueError: cannot reindex from a duplicate axis
。
更新:这里有一些数据和代码来重现这个问题:
data = {'month': ['2014-01-01', '2014-02-01', '2014-03-01'],
'num_percent': [0.4, 0.5, 0.6]}
df1 = pd.DataFrame(data)
df1['month'] = pd.to_datetime(df1['month'])
df1 = df1.set_index('month')
data = {'month': ['2014-01-01', '2014-02-01', '2014-03-01', '2014-01-01'],
'org': ['00K', '00K', '00K', '00L'],
'total_quantity': [1000, 1000, 2000, 1000]}
df2 = pd.DataFrame(data)
df2['month'] = pd.to_datetime(df2['month'])
df2 = df2.set_index('month')
# Both of these produce ValueError: cannot reindex...
df2['percent'] = df1['num_percent'] * df2['total_quantity']
df2.loc[df2.index.isin(df1.index), 'percent'] = df2['total_quantity'] * df1['num_percent']
最佳答案
如果你join
首先是 dfs 然后你可以相乘:
In [24]:
df3 = df1.join(df2)
df3['percent'] = df3['num_percent'] * df3['total_quantity']
df3
Out[24]:
num_percent org total_quantity percent
month
2014-01-01 0.4 00K 1000 400
2014-01-01 0.4 00L 1000 400
2014-02-01 0.5 00K 1000 500
2014-03-01 0.6 00K 2000 1200
关于python - Pandas :从另一个数据框中逐列相乘?,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/34853397/