Pandas DataFrame ApplyMap 方法
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Pandas DataFrame ApplyMap method
提问by Baktaawar
I wanted to try out the functionality of applymapmethod of Pandas DataFrameobject. Here is the Use case:
我想尝试applymapPandasDataFrame对象的方法的功能。这是用例：
Let say my DataFrame df1is as follows:
假设我的 DataFramedf1如下：
Age ID Name
0 27 101 John
1 22 102 Bob
2 19 103 Alok
3 27 104 Tom
4 32 105 Matt
5 19 106 Steve
6 5 107 Tom
7 55 108 Dick
8 67 109 Harry
Now I want to create a flag variable with the logic that if length of element is less than 2, then flag=1 else flag=0.
现在我想创建一个标志变量，其逻辑是如果元素的长度小于 2，则标志 = 1 否则标志 = 0。
In order to run this element-wise, I wanted to use applymapmethod. So for that I created a user defined function as follows:
为了逐个运行这个元素，我想使用applymap方法。为此，我创建了一个用户定义的函数，如下所示：
def f(x):
if len(str(x))>2:
df1['Flag']=1
else:
df1['Flag']=0
Then I ran df1.applymap(f)which gave:
然后我跑了df1.applymap(f)它给：
Age ID Name
0 None None None
1 None None None
2 None None None
3 None None None
4 None None None
5 None None None
6 None None None
7 None None None
8 None None None
instead of creating a flag variable with the flag value. How can I achieve the desired functionality using applymap?
而不是使用标志值创建标志变量。如何使用 实现所需的功能applymap？
Can't we use the DataFrame variable name or pandas statement inside the user defined function? I.e., is df1['Flag']valid inside the definition of f()?
我们不能在用户定义的函数中使用 DataFrame 变量名或 pandas 语句吗？即，df1['Flag']在f()?的定义内是否有效？
回答by Bonlenfum
the function f(x)is not special to pandas -- it is just a regular python function. So the only data in scope within fis the variable xOther members of df1are not available.
该函数f(x)对于pandas 并不特殊——它只是一个普通的python 函数。因此，范围内的唯一数据f是变量xOther 的成员df1不可用。
From applymapdocs:
来自applymap文档：
func : function
Python function, returns a single value from a single value
功能：功能
Python 函数，从单个值返回单个值
So you could try this:
所以你可以试试这个：
def f(x):
if len(str(x)) <= 3: return 1
else: return 0
Outputting 1/0 for each element in the frame when applied:
应用时为框架中的每个元素输出 1/0：
df1.applymap(f)
>>>
Age ID Name
0 1 1 0
1 1 1 1
2 1 1 0
3 1 1 1
4 1 1 0
5 1 1 0
6 1 1 1
7 1 1 0
8 1 1 0
To use the result to add another variable in each row, you need one value per row , e.g.,
要使用结果在每一行中添加另一个变量，您需要每行一个值，例如，
df1['Flag'] = df1.applymap(f).all(axis=1).astype(bool)
>>> df1
Age ID Name Flag
0 27 101 John False
1 22 102 Bob True
2 19 103 Alok False
3 27 104 Tom True
4 32 105 Matt False
5 19 106 Steve False
6 5 107 Tom True
7 55 108 Dick False
8 67 109 Harry False
Also check out https://stackoverflow.com/a/19798528/1643946which covers apply, mapas well as applymap.
还检查了https://stackoverflow.com/a/19798528/1643946覆盖apply，map以及applymap。
