我有一个带有3列的类和5行的学生中的dataframe。其中一些学生是重复的。我想从所有类中列出最常见的学生名称，并以降序列出它们，它们存在的次数以及它们存在的课程。

df = pd.DataFrame({
    'biology': ['ryan', 'sarah', 'tom', 'ed', 'jackson'],
    'statistics': ['sarah', 'ed', 'jacob', 'ryan', 'de'],
    'ecology': ['austin', 'ryan', 'tom', 'sam', 'sarah']
})

   biology statistics ecology
0     ryan      sarah  austin
1    sarah         ed    ryan
2      tom      jacob     tom
3       ed       ryan     sam
4  jackson         de   sarah

我希望输出看起来像这样：

ryan, 3 classes, (biology, statistics, ecology)
sarah, 3 classes, (biology, statistics, ecology)
tom, 2 classes, (biology, ecology)
ed, 2 classes, (biology, statistics)
jackson, 1 class, (biology)
jacob, 1 class, (statistics)
de, 1 class, (statistics)
austin, 1 class, (ecology)

...等等

任何帮助都会受到欣赏，我是一个初学者，所以我已经这样几个小时了。大脑被杀。谢谢！

分析解答

我们可以melt. the dataframe来长期形成，然后groupby aggregate.与命名聚合来获取类的数量，以及类的名称，最后我们可以先获得最高频率的学生：

output_df = (
    df.melt(var_name='class name', value_name='student name')
        .groupby('student name', as_index=False)
        .agg(class_count=('class name', 'count'),
             classes=('class name', tuple))
        .sort_values('class_count', ascending=False, ignore_index=True)
)

output_df：

  student name  class_count                         classes
0         ryan            3  (biology, statistics, ecology)
1        sarah            3  (biology, statistics, ecology)
2           ed            2           (biology, statistics)
3          tom            2              (biology, ecology)
4       austin            1                      (ecology,)
5           de            1                   (statistics,)
6      jackson            1                      (biology,)
7        jacob            1                   (statistics,)
8          sam            1                      (ecology,)

我们可以在条件上将classes/class添加到class_count并写入to_csv.：

# Conditionally Add Classes/Class
output_df['class_count'] = output_df['class_count'].astype(str) + np.where(
    output_df['class_count'].eq(1),
    ' class',
    ' classes'
)
# Write to CSV
output_df.to_csv('output.csv', index=False, header=None)

output.csv：

ryan,3 classes,"('biology', 'statistics', 'ecology')"
sarah,3 classes,"('biology', 'statistics', 'ecology')"
ed,2 classes,"('biology', 'statistics')"
tom,2 classes,"('biology', 'ecology')"
austin,1 class,"('ecology',)"
de,1 class,"('statistics',)"
jackson,1 class,"('biology',)"
jacob,1 class,"('statistics',)"
sam,1 class,"('ecology',)"

设置和import：

import numpy as np
import pandas as pd

df = pd.DataFrame({
    'biology': ['ryan', 'sarah', 'tom', 'ed', 'jackson'],
    'statistics': ['sarah', 'ed', 'jacob', 'ryan', 'de'],
    'ecology': ['austin', 'ryan', 'tom', 'sam', 'sarah']
})