将 grouby dict_keys 转换为带有键值的字典

Question

对于下面给出的示例文件，go 如何将groupby键转换为字典，然后将 integer 数字分配给键？ 我希望最终能够遍历字典，从字典中为每个相应的键提取数字。

到目前为止，这是我的代码：

import math
import pandas as pd

original_df = pd.read_csv('NewDatasetTotal4.csv')

original_df = original_df.astype(str)
length = original_df.original_class.count()

group_size =  original_df.groupby('original_class').size()

colum_to_grab = 'original_class'
group_list = original_df.groupby(colum_to_grab)

# How to now convert the group_list.groups.keys() to a dictionary with
# pigs_size = 5
# goats_size = 3
# chickens_size = 7
# hens_size = 7
# sheep_size = 2

分配的整数可以在[5, 3, 7, 7, 2]之类的数组中吗

这是我的数据文件：

slice_file_name fsID    start   end salience    fold    classID class_name  original_class
1-1000020520400.wav                 1   1   pigs    
1-100004024000001.wav                   1   1   pigs    
1-10000406050001.wav                    1   1   pigs    
1-1000050120400.wav                 1   1   pigs    
1-1000050320400.wav                 1   1   pigs    
1-1000050520400.wav                 1   2   goats   
1-10000601400001000.wav                 1   2   goats   
1-1000060340000.wav                 1   2   goats   
1-100006070500.wav                  1   3   chickens    
1-100007020800.wav                  1   3   chickens    
1-100007024000001.wav                   1   3   chickens    
1-1000070320400.wav                 1   3   chickens    
1-100007050800.wav                  1   3   chickens    
1-100007064000001.wav                   1   3   chickens    
1-100010620400.wav                  1   3   chickens    
1-100040620400.wav                  1   3   chickens    
1-10006020500.wav                   1   3   chickens    
1-10006030500.wav                   1   3   chickens    
1-100060520400.wav                  1   4   hens    
1-10007020500.wav                   1   4   hens    
2-100070420400.wav                  1   4   hens    
2-100070540000.wav                  1   4   hens    
2-1313131313004.wav                 1   4   hens    
2-1313131313043.wav                 1   4   hens    
2-1313131313044.wav                 1   5   sheep   
2-150002020500.wav                  1   5   sheep   
2-150002060800.wav                  1   5   sheep   
2-150004022040001.wav                   1   5   sheep   
2-15000406050001.wav                    1   5   sheep   
2-150006014000001.wav                   1   5   sheep   
2-150006024000001.wav                   1   5   sheep

Answer 1

如果我理解正确，你可以这样做：

out = {k: g.shape[0] for k, g in df.groupby("original_class")}
print(out)

这打印：

{"chickens": 10, "goats": 3, "hens": 6, "pigs": 5, "sheep": 7}

---

编辑：

lst = [5, 3, 2, 4, 2]

out = {k: v for (k, _), v in zip(df.groupby("original_class"), lst)}
print(out)

印刷：

{'chickens': 5, 'goats': 3, 'hens': 2, 'pigs': 4, 'sheep': 2}