在不使用索引的情况下替换pandas DataFrame中所选单元格的值

this is a rather similar question to this question but with one key difference: I'm selecting the data I want to change not by its index but by some criteria.

对于这个问题,这是一个相当类似的问题,但有一个关键的区别:我选择的数据不是通过索引而是通过某些标准来改变。

If the criteria I apply return a single row, I'd expect to be able to set the value of a certain column in that row in an easy way, but my first attempt doesn't work:

如果我应用的条件返回单行,我希望能够以一种简单的方式设置该行中某列的值,但我的第一次尝试不起作用:

>>> d = pd.DataFrame({'year':[2008,2008,2008,2008,2009,2009,2009,2009], 
...                   'flavour':['strawberry','strawberry','banana','banana',
...                   'strawberry','strawberry','banana','banana'],
...                   'day':['sat','sun','sat','sun','sat','sun','sat','sun'],
...                   'sales':[10,12,22,23,11,13,23,24]})

>>> d
   day     flavour  sales  year
0  sat  strawberry     10  2008
1  sun  strawberry     12  2008
2  sat      banana     22  2008
3  sun      banana     23  2008
4  sat  strawberry     11  2009
5  sun  strawberry     13  2009
6  sat      banana     23  2009
7  sun      banana     24  2009

>>> d[d.sales==24]
   day flavour  sales  year
7  sun  banana     24  2009

>>> d[d.sales==24].sales = 100
>>> d
   day     flavour  sales  year
0  sat  strawberry     10  2008
1  sun  strawberry     12  2008
2  sat      banana     22  2008
3  sun      banana     23  2008
4  sat  strawberry     11  2009
5  sun  strawberry     13  2009
6  sat      banana     23  2009
7  sun      banana     24  2009

So rather than setting 2009 Sunday's Banana sales to 100, nothing happens! What's the nicest way to do this? Ideally the solution should use the row number, as you normally don't know that in advance!

因此,没有将2009年周日的香蕉销量设定为100,而是没有任何反应!最好的方法是什么?理想情况下,解决方案应使用行号,因为您通常不提前知道!

Many thanks in advance, Rob

非常感谢,Rob

2 个解决方案

#1

Many ways to do that

许多方法都是这样做的

1

In [7]: d.sales[d.sales==24] = 100

In [8]: d
Out[8]: 
   day     flavour  sales  year
0  sat  strawberry     10  2008
1  sun  strawberry     12  2008
2  sat      banana     22  2008
3  sun      banana     23  2008
4  sat  strawberry     11  2009
5  sun  strawberry     13  2009
6  sat      banana     23  2009
7  sun      banana    100  2009

2

In [26]: d.loc[d.sales == 12, 'sales'] = 99

In [27]: d
Out[27]: 
   day     flavour  sales  year
0  sat  strawberry     10  2008
1  sun  strawberry     99  2008
2  sat      banana     22  2008
3  sun      banana     23  2008
4  sat  strawberry     11  2009
5  sun  strawberry     13  2009
6  sat      banana     23  2009
7  sun      banana    100  2009

3

In [28]: d.sales = d.sales.replace(23, 24)

In [29]: d
Out[29]: 
   day     flavour  sales  year
0  sat  strawberry     10  2008
1  sun  strawberry     99  2008
2  sat      banana     22  2008
3  sun      banana     24  2008
4  sat  strawberry     11  2009
5  sun  strawberry     13  2009
6  sat      banana     24  2009
7  sun      banana    100  2009

#2

Not sure about older version of pandas, but in 0.16 the value of a particular cell can be set based on multiple column values.

不确定旧版本的pandas,但在0.16中,可以根据多个列值设置特定单元格的值。

Extending the answer provided by @waitingkuo, the same operation can also be done based on values of multiple columns.

扩展@waitingkuo提供的答案,也可以根据多列的值完成相同的操作。

d.loc[(d.day== 'sun') & (d.flavour== 'banana') & (d.year== 2009),'sales'] = 100

#1