使用前一个“行"的值在 pandas 系列中 [英] Using the values of a previous "row" in a pandas series

问题描述

我有一个看起来像这样的 CSV(当带入一个带有read_csv()，看起来一样).

I have a CSV that looks like this (and when brought into a pandas Dataframe with read_csv(), it looks the same).

我想根据以下逻辑更新 ad_requests 列中的值:

I want to update the values in column ad_requests according to the following logic:

对于给定的行，如果 ad_requests 有值，请不要管它.否则，将前一行的 ad_requests 值减去前一行的 impressions 值.所以在第一个例子中，我们希望得到:

For a given row, if ad_requests has a value, leave it alone. Else, give it a value of the previous row's value for ad_requests minus the previous row's value for impressions. So in the first example, we would like to end up with:

我部分到达那里:

df["ad_requests"] = [i if not pd.isnull(i) else ??? for i in df["ad_requests"]]

这就是我卡住的地方.在 else 之后，我想返回"并访问前一个行"，尽管我知道这不是 Pandas 的使用方式.另一件要注意的事情是，行将始终按列ad_tag_name 分为三组.如果我 pd.groupby["ad_tag_name"]，然后我可以把它变成一个 list 并开始切片和索引，但同样，我认为必须有更好的方法在熊猫中做到这一点(因为有很多事情).

And this is where I get stuck. After the else, I want to "go back" and access the previous "row", though I know that this is not how pandas is meant to be used. Another thing to note that is the rows will always be grouped in threes, by column ad_tag_name. If I pd.groupby["ad_tag_name"], I can then turn this into a list and start slicing and indexing, but again, I think there must be a better way to do this in pandas (as there is many things).

Python:2.7.10

Python: 2.7.10

熊猫:0.18.0

推荐答案

你会想要做这样的事情:

You'll want to do something like this:

pd.options.mode.chained_assignment = None #suppresses "SettingWithCopyWarning"
for index, elem in enumerate(df['ad_requests']):
    if pd.isnull(elem):
        df['ad_requests'][index]=df['ad_requests'][index-1]-df['impressions'][index-1]

警告来自这样一个事实，即我们正在更改数据框视图的值，这会影响原始数据框.然而，这正是我们想要做的，所以我们并不真正关心.

The warning comes from the fact that we're changing the values of a view of a dataframe, which affects the original dataframe. That is what we wish to do, however, so it doesn't really concern us.

(Python 2.7.12 和 Pandas 0.19.0)

(Python 2.7.12 and Pandas 0.19.0)

修改最后一行代码

df['ad_requests'][index]=df['ad_requests'][index-1]-df['impressions'][index-1]

到

df.at[index,'ad_requests']=df.at[index-1,'ad_requests']-df.at[index-1,'impressions']

消除了抑制任何警告的需要:

removes the need to suppress any warnings:

for index, elem in enumerate(df['ad_requests']):
    if pd.isnull(elem):
        df.at[index,'ad_requests']=df.at[index-1,'ad_requests']-df.at[index-1,'impressions']

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