Pandas基于现有列值填充新列

Question

我有以下数据帧df_shots：

              TableIndex  MatchID  GameWeek           Player  ...      ShotPosition    ShotSide      Close             Position
ShotsDetailID                                                 ...                                                              
6                      5    46605         1  Roberto Firmino  ...  very close range         N/A      close  very close rangeN/A
8                      7    46605         1  Roberto Firmino  ...           the box  the centre  not close    the boxthe centre
10                     9    46605         1  Roberto Firmino  ...           the box    the left  not close      the boxthe left
17                    16    46605         1  Roberto Firmino  ...           the box  the centre      close    the boxthe centre
447                  446    46623         2  Roberto Firmino  ...           the box  the centre      close    the boxthe centre
...                  ...      ...       ...              ...  ...               ...         ...        ...                  ...
6656                6662    46870        27  Roberto Firmino  ...  very close range         N/A      close  very close rangeN/A
6666                6672    46870        27  Roberto Firmino  ...           the box   the right  not close     the boxthe right
6674                6680    46870        27  Roberto Firmino  ...           the box  the centre  not close    the boxthe centre
6676                6682    46870        27  Roberto Firmino  ...           the box    the left  not close      the boxthe left
6679                6685    46870        27  Roberto Firmino  ...   outside the box         N/A  not close   outside the boxN/A

为清楚起见，所有可能的“位置”值为：

positions = ['a difficult anglethe left',
             'a difficult anglethe right',
             'long rangeN/A',
             'long rangethe centre',
             'long rangethe left',
             'long rangethe right',
             'outside the boxN/A',
             'penaltyN/A',
             'the boxthe centre',
             'the boxthe left',
             'the boxthe right',
             'the six yard boxthe left',
             'the six yard boxthe right',
             'very close rangeN/A']

现在，我想将以下x/y值映射到每个“位置”名称，并将该值存储在新的“位置XY”列下：

    the_boxthe_center = {'y':random.randrange(25,45), 'x':random.randrange(0,6)}
    the_boxthe_left = {'y':random.randrange(41,54), 'x':random.randrange(0,16)}
    the_boxthe_right = {'y':random.randrange(14,22), 'x':random.randrange(0,16)}
    very_close_rangeNA = {'y':random.randrange(25,43), 'x':random.randrange(0,4)}
    six_yard_boxthe_left = {'y':random.randrange(33,43), 'x':random.randrange(4,6)}
    six_yard_boxthe_right = {'y':random.randrange(25,33), 'x':random.randrange(4,6)}
    a_diffcult_anglethe_left = {'y':random.randrange(43,54), 'x':random.randrange(0,6)}
    a_diffcult_anglethe_right = {'y':random.randrange(14,25), 'x':random.randrange(0,6)}
    penaltyNA = {'y':random.randrange(36), 'x':random.randrange(8)}
    outside_the_boxNA = {'y':random.randrange(14,54), 'x':random.randrange(16,28)}
    long_rangeNA = {'y':random.randrange(0,68), 'x':random.randrange(40,52)}
    long_rangethe_centre = {'y':random.randrange(0,68), 'x':random.randrange(28,40)}
    long_rangethe_right = {'y':random.randrange(0,14), 'x':random.randrange(0,24)}
    long_rangethe_left = {'y':random.randrange(54,68), 'x':random.randrange(0,24)}

---

我试过：

if df_shots['Position']=='very close rangeN/A':
        df_shots['Position X/Y']==very_close_rangeNA
...# and so on

但我得到：

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

---

我该怎么做

Answer 1

在一个容器外存储这么多相关变量是一种糟糕的形式，让我们使用映射到数据帧的字典

data_dict = 
{'the boxthe centre': {'y':random.randrange(25,45)...}


df['Position'] = df['Position'].map(data_dict)

print(df['Position'])
6        {'y': 35, 'x': 2}
8        {'y': 32, 'x': 1}
10      {'y': 44, 'x': 11}
17       {'y': 32, 'x': 1}
447      {'y': 32, 'x': 1}
...                    NaN
6656     {'y': 35, 'x': 2}
6666    {'y': 15, 'x': 11}
6674     {'y': 32, 'x': 1}
6676    {'y': 44, 'x': 11}
6679    {'y': 37, 'x': 16}
Name: Position, dtype: object

Answer 2

下面是一些代码，它们可能会达到您想要的效果

首先创建一个列表，列出你所有的“位置XY”，如

position_xy = [the_boxthe_center,the_boxthe_left,....,long_rangethe_left] #and so on...

以及相应的positions列表（如您已经拥有的） 然后我建议你做一个字典，这样每个位置都会进行相应的位置xy计算

dict_positionxy = dict(zip(position, position_xy))

然后在数据框中创建一个新列，在其中根据位置存储x，y值

 df_shots['Position X/Y'] = 0.

现在一行一行地遍历所有行

for index, row in df_shots.iterrows():
    for key, values in dict_positionxy.items():

       if row['Position'] == key:
           #row['Position X/Y'] = value
           df_shots.at[index,’Position X/Y’]= value

print(df_shots)

这应该可以做到：）

Answer 3

下面是一些示例代码，可以实现您想要的功能。我创建了一个基本的df_快照模型，但是在更大的数据帧上应该运行相同的模型。我还将一些自由变量存储在dict中，以简化筛选

应该注意的是，因为预先计算了positions_xy的随机值，所以每个放炮位置的所有x/y值都是相同的。这可能不是你想要的

import pandas as pd
import random

# Sample df_shots
df_shots = pd.DataFrame({'Position': ['the_boxthe_center', 'the_boxthe_left']})

# Store position/xy pairs in dict
positions_xy = {'the_boxthe_center': {'y': random.randrange(25, 45), 'x': random.randrange(0, 6)},
                'the_boxthe_left': {'y': random.randrange(41, 54), 'x': random.randrange(0, 16)}}

# Create new column
df_shots['Position XY'] = ''

# Iterate over all position/xy pairs
for position, xy in positions_xy.items():
    # Determine indices of all players that match
    matches = df_shots['Position'] == position
    matches_indices = matches[matches].index
    # Update matching rows in df_shots with xy
    for idx in matches_indices:
        df_shots.at[idx, 'Position XY'] = xy

print(df_shots)

产出：

            Position        Position XY
0  the_boxthe_center  {'y': 36, 'x': 2}
1    the_boxthe_left  {'y': 44, 'x': 0}