在Pandas中创建带有数字的新列以与具有现有数字的列分组 [英] Creating a new column with numbers in Pandas to group with a column with existing numbers

问题描述

美好的一天

我在这里有一个数据框的列:

I have a column from a data frame here:

 A
 23
 10
 11 
 22

我的目标是创建一个新列并关联数字，如下所示:

My objective is to create a new column and associate the numbers like this:

A     file_number
23        8
10        6
11        6
22        8

如上所示，数字22、23都与数字8相关联，数字10和11与数字6相关联.如何创建这样的列?预先感谢

As seen above both numbers 22, 23 are associated with the number 8 and numbers 10 and 11 are associated with number 6. How can I create such a column? Thanks in advance

推荐答案

我认为如果需要使用 map :

I think need if need create new values by first value of number with map by dictionary:

print (df['A'].apply(type))
0    <class 'int'>
1    <class 'int'>
2    <class 'int'>
3    <class 'int'>
Name: A, dtype: object

df['new'] = (df['A'] // 10).map({1:6, 2:8})
print (df)
    A  new
0  23    8
1  10    6
2  11    6
3  22    8

详细信息:

print ((df['A'] // 10))
0    2
1    1
2    1
3    2
Name: A, dtype: int64

另一种适用于字符串的解决方案:

Another solution works with strings:

df['new'] = df['A'].astype(str).str[0].map({'1':6, '2':8})

---

print (df['A'].apply(type))
0    <class 'str'>
1    <class 'str'>
2    <class 'str'>
3    <class 'str'>
Name: A, dtype: object

df['new'] = df['A'].str[0].map({'1':6, '2':8})

如果可能需要将正数转换为第一个数字，请使用此解决方案转换为numpy/pandas:

If need convert positive number to first numeric is possible use this solution converted to numpy/pandas:

df['new'] = df['A'] // 10 ** np.log10(df['A'].values).astype(int)

print (df)
        A  new
0       2    2
1   10000    1
2     110    1
3  220000    2

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