如何用Pandas填写范围内的缺失值? [英] How can I fill in a missing values in range with Pandas?

问题描述

我有一个数据集，其中包含许多如下所示的值.

I have a dataset with a number of values like below.

>>> a.head()
   value  freq
3      9     1
2     11     1
0     12     4
1     15     2

我需要在value列中的整数之间填写值.例如，我需要在9&之间插入一个新行. 11填充零，然后在12-15之间再填充两个.最终结果应该是9-15的数据集，其中缺失"行全为零.

I need to fill in the values between the integers in the value column. For example, I need to insert one new row between 9 & 11 filled with zeroes, then another two between 12-15. The end result should be the dataset with 9-15 with 'missing' rows as zeroes across the board.

总有没有在不替换数据的情况下在特定位置插入新行的情况?我发现的唯一方法是在一个位置上切片数据帧，然后追加新行并连接其余部分.

Is there anyway to insert a new row at an specific location without replacing data? The only methods I've found involve slicing the dataframe at a location then appending a new row and concatenating the remainder.

更新:索引完全无关紧要，所以不必担心.

UPDATE: The index is completely irrelevant so don't worry about that.

推荐答案

您没有说索引会发生什么，所以我认为它并不重要.

You didn't say what should happen to your Index, so I'm assuming it's unimportant.

In [12]: df.index = df['value']

In [15]: df.reindex(np.arange(df.value.min(), df.value.max() + 1)).fillna(0)
Out[15]:
       value  freq
value
9          9     1
10         0     0
11        11     1
12        12     4
13         0     0
14         0     0
15        15     2

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