[英]Lambda function notation in Pandas
I received a wonderful lambda function from a user a while ago. 前一段时间,我从用户那里收到了一个很棒的lambda函数。
actresses_modified['Winner_Count'] = actresses_modified.apply(lambda x: actresses_modified.Name.value_counts()[x.Name], axis=1)
The data frame to which it is applied looks like this: 将其应用于的数据帧如下所示:
Year Award Winner Name
2 1928 Best Actress 0.0 Louise Dresser
3 1928 Best Actress 1.0 Janet Gaynor
4 1928 Best Actress 0.0 Gloria Swanson
40 1929 Best Actress 0.0 Ruth Chatterton
41 1929 Best Actress 0.0 Betty Compson
The problem is I have forgotten how it works (I had to step away from this "for fun" project) and, more specifically, exactly what is going on with [x.Name]
. 问题是我忘记了它是如何工作的(我不得不离开这个“取乐”项目),更具体地说,正是[x.Name]
发生了什么。
The line actresses_modified.Name.value_counts()
by itself gives me the count of all actress names in the data frame. 行actresses_modified.Name.value_counts()
本身给了我数据框中所有女演员的人数。 What does [x.Name] mean in english, how does it manage to tally up all of the 1s next to each person's name in the data frame's Winner column, and return a correct tally of the total number of wins? [x.Name]在英语中是什么意思,它如何设法对数据框的“获胜者”列中每个人的名字旁边的所有1进行汇总,并返回正确的总获胜次数? Of equal importance, does this type of syntax have a name? 同样重要的是,这种语法是否有名称? My google searches turned up nada. 我的Google搜索结果显示为nada。
Any thoughts would be appreciated? 任何想法将不胜感激?
Here, I'm not sure I made myself clear in the comment. 在这里,我不确定我是否在评论中表达了自己的意思。 So the apply
method "Applies function along input axis of DataFrame." 因此, apply
方法“沿DataFrame的输入轴应用功能”。 So let's say, for simplicity's sake, that we have a collection of Actress objects called actresses_modified and it looks like this: 因此,为简单起见,我们假设有一个Actress对象集合,称为actresses_modified,它看起来像这样:
actresses_modified = [<Actress>, <Actress>, <Actress>, <Actress>]
Let's assume that this is how the Actress
is defined: 让我们假设这是Actress
的定义方式:
class Actress:
Name = "Some String"
So then we have our lambda function which gets applied to each actress in the collection as x
. 因此,我们有了lambda函数,该函数将作为x
应用于集合中的每个女演员。 value_counts()
returns "object containing counts of unique values." value_counts()
返回“包含唯一值计数的对象”。
So when we call value_counts()
for each actress we're getting that Actress's counts value by key. 因此,当我们为每个女演员调用value_counts()
,我们将获得女演员的按值计数。 Let's pretend that value_counts()
returns a dict with actress names and their "count" and it looks like this: 让我们假设value_counts()
返回一个包含女演员名称及其“ count”的字典,它看起来像这样:
counts = {
'Jane Doe': 1,
'Betty Ross': 3,
}
And we have our Actress objects with actress 1's Name
is "Jane Doe", so when we call value_counts()[x.Name]
we're doing counts["Jane Doe"]
which would return 1. 而且我们的Actress对象的女演员1的Name
是“ Jane Doe”,因此当我们调用value_counts()[x.Name]
我们正在做value_counts()[x.Name]
counts["Jane Doe"]
,该返回值是1。
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