基于单列在熊猫中创建一系列数字

时间:2021-04-02 10:27:57

标签: python pandas

我有一个熊猫数据框:

df2 = pd.DataFrame({'ID':['A','B','C','D','E'], 'loc':['Lon','Tok','Ber','Ams','Rom'], 'start':[20,10,30,40,43]})


    ID  loc     start
0   A   Lon     20
1   B   Tok     10
2   C   Ber     30
3   D   Ams     40
4   E   Rom     43

我希望添加一个名为 range 的列,该列采用 'start' 中的值并生成一系列值(包括初始值),这些值(包括初始值)比初始值小 10,所有值都在同一行中。< /p>

所需的输出:

    ID  loc     start    range
0   A   Lon     20       20,19,18,17,16,15,14,13,12,11,10
1   B   Tok     10       10,9,8,7,6,5,4,3,2,1,0
2   C   Ber     30       30,29,28,27,26,25,24,23,22,21,20
3   D   Ams     40       40,39,38,37,36,35,34,33,32,31,30
4   E   Rom     43       43,42,41,40,39,38,37,36,35,34,33

我试过了:

df2['range'] = [i for i in range(df2.start, df2.start -10)]

def create_range2(row):
  
  return df2['start'].between(df2.start, df2.start - 10)
  

df2.loc[:, 'range'] = df2.apply(create_range2, axis = 1)

但是我似乎无法获得所需的输出。我打算将此解决方案应用于多个数据帧,其中一个具有 > 2,000,000 行。

谢谢

2 个答案:

答案 0 :(得分:0)

这行得通吗?

df2['range'] = df2.apply(lambda row: list(range(row['start'],row['start']-11,-1)),axis=1)
df2

输出


    ID  loc start   range
0   A   Lon 20  [20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10]
1   B   Tok 10  [10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0]
2   C   Ber 30  [30, 29, 28, 27, 26, 25, 24, 23, 22, 21, 20]
3   D   Ams 40  [40, 39, 38, 37, 36, 35, 34, 33, 32, 31, 30]
4   E   Rom 43  [43, 42, 41, 40, 39, 38, 37, 36, 35, 34, 33]

或者如果你想用逗号分隔:

df2['range'] = df2.apply(lambda row: ','.join([str(v) for v in range(row['start'],row['start']-11,-1)]),axis=1)

得到

    ID  loc start   range
0   A   Lon 20  20,19,18,17,16,15,14,13,12,11,10
1   B   Tok 10  10,9,8,7,6,5,4,3,2,1,0
2   C   Ber 30  30,29,28,27,26,25,24,23,22,21,20
3   D   Ams 40  40,39,38,37,36,35,34,33,32,31,30
4   E   Rom 43  43,42,41,40,39,38,37,36,35,34,33

答案 1 :(得分:0)

您可以准备范围创建函数并.apply它以如下方式开始列:

import pandas as pd
df2 = pd.DataFrame({'ID':['A','B','C','D','E'], 'loc':['Lon','Tok','Ber','Ams','Rom'], 'start':[20,10,30,40,43]})
def make_10(x):
    return list(range(x, x-10-1, -1))
df2["range"] = df2["start"].apply(make_10)
print(df2)

输出

  ID  loc  start                                         range
0  A  Lon     20  [20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10]
1  B  Tok     10            [10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0]
2  C  Ber     30  [30, 29, 28, 27, 26, 25, 24, 23, 22, 21, 20]
3  D  Ams     40  [40, 39, 38, 37, 36, 35, 34, 33, 32, 31, 30]
4  E  Rom     43  [43, 42, 41, 40, 39, 38, 37, 36, 35, 34, 33]

说明:.applypandas.Series 方法(pandas.DataFrame 的列)接受按元素应用的函数。请注意,-1 中有 range,因为它是包含-不包含的,而 -1 作为步长,因为您希望使用降序值。