从具有重复项的数据集创建一个数据透视表 table

Question

我正在尝试根据此 dataset（性别薪酬）

创建数据透视图 table 和热图

我的代码是：

df = df.pivot('Seniority', 'TotalPay', 'Gender')

ax = sns.heatmap(df)

但是我得到一个错误：

KeyError                                  Traceback (most recent call last)
/usr/local/lib/python3.7/dist-packages/pandas/core/indexes/base.py in get_loc(self, 
key, method, tolerance)
    3360             try:
-> 3361                 return self._engine.get_loc(casted_key)
   3362             except KeyError as err:

6 frames
pandas/_libs/hashtable_class_helper.pxi in 
pandas._libs.hashtable.PyObjectHashTable.get_item()

pandas/_libs/hashtable_class_helper.pxi in 
pandas._libs.hashtable.PyObjectHashTable.get_item()

KeyError: 'Gender'

The above exception was the direct cause of the following exception:

KeyError                                  Traceback (most recent call last)
/usr/local/lib/python3.7/dist-packages/pandas/core/indexes/base.py in get_loc(self, 
key, method, tolerance)
   3361                 return self._engine.get_loc(casted_key)
   3362             except KeyError as err:
-> 3363                 raise KeyError(key) from err
   3364 
   3365         if is_scalar(key) and isna(key) and not self.hasnans:

KeyError: 'Gender'

谁能帮我解决这个问题？我尝试使用 drop_duplicates() 删除重复项，但仍然无效。非常感谢。

Answer 1

我的猜测是，我创建代码时的理解是我想创建一个按年份和性别划分的每月和奖金总额的热图。我发布这个是因为发问者给了我一个回应的机会。要索引的 SENIORITY 的分组是主元中错误的原因，已被消除。旋转和转换热图的数据。

import pandas as pd
import seaborn as sns

df = pd.read_csv('/content/Glassdoor Gender Pay Gap.csv', sep=';')
df['TotalPay'] = df['BasePay'] + df['Bonus']

df.head()
JobTitle    Gender  Age     PerfEval    Education   Dept    Seniority   BasePay     Bonus   TotalPay
0   Graphic Designer    Female  18  5   College     Operations  2   42363   9938    52301
1   Software Engineer   Male    21  5   College     Management  5   108476  11128   119604
2   Warehouse Associate     Female  19  4   PhD     Administration  5   90208   9268    99476
3   Software Engineer   Male    20  5   Masters     Sales   4   108080  10154   118234
4   Graphic Designer    Male    26  5   Masters     Engineering     5   99464   9319    108783

df = df.groupby(['Seniority', 'Gender'])['TotalPay'].sum().to_frame('TotalPay').reset_index()

df.head()
    Seniority   Gender  TotalPay
0   1   Female  6267525
1   1   Male    9892202
2   2   Female  8738918
3   2   Male    10224439
4   3   Female  10359925

df = df.pivot('Seniority', 'Gender', 'TotalPay')
df
Gender  Female  Male
Seniority       
1   6267525     9892202
2   8738918     10224439
3   10359925    11775112
4   8483675     11932083
5   11273034    11992901

sns.heatmap(df, annot=True, fmt=',')

从具有重复项的数据集创建一个数据透视表 table

create a pivot table from a dataset with duplicates

python

pandas

numpy

pivot-table

heatmap