英文:
Find mode in panda Dataframe
问题
在c1_ind和c2_ind中查找众数，我不想沿每列查找。
在c1_ind和c3_ind中查找众数。
英文:
Find mode among all values in c1_ind and c2_ind . I don't want to mode along each column.
import pandas as pd
import numpy as np
from scipy.stats import mode
list =[{"col1":123,"C1_IND ":"Rev","C2_IND":"Hold"},
{"col1":456,"C1_IND ":"Hold","C2_IND":"Rev"},
{"col1":123,"C1_IND ":"Hold","C2_IND":"Service"},
{"col1":1236,"C1_IND ":"Man","C2_IND":"Man"}]
df = pd.DataFrame.from_dict(list)
print(df)
For another example Find mode among all values in c1_ind and c3_ind
import pandas as pd
import numpy as np
from scipy.stats import mode
list =[{"col1":123,"C1_IND ":"Rev","C2_IND":"Hold","C3_IND":"Hold"},
{"col1":456,"C1_IND ":"Hold","C2_IND":"Rev","C3_IND":"Rev"},
{"col1":123,"C1_IND ":"Hold","C2_IND":"Service","C3_IND":"Service"},
{"col1":1236,"C1_IND ":"Man","C2_IND":"Man","C3_IND":"Man"}]
df = pd.DataFrame.from_dict(list)
print(df)
答案1
得分: 1
你可以使用 filter 来选择感兴趣的列（这里使用正则表达式），然后使用 stack，最后使用 mode。:
df.filter(regex='C\d+_IND').stack().mode().iloc[0]
注意：如果有多个众数，我们只保留一个。如果你想要全部，去掉 iloc[0]，可选替换为 squeeze。
输出: 'Hold'
英文:
You can use filter to select the columns of interest (here by regex), then stack and finally use mode.:
df.filter(regex='C\d+_IND').stack().mode().iloc[0]
NB. If there are several modes, we only keep one. If you want all, remove the iloc[0], optionally replacing with squeeze.
Output: 'Hold'
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