如何在机器学习中打印分类特征？

Question

假设我有一个火车数据集

r1：便宜，昂贵->价格

r2：兴奋->娱乐

r3：炎热，夏天->天气

r4：金钱->价格

r5：下雨->天气

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然后我要以这种模式显示它：

价格->便宜，昂贵，钱

娱乐->兴奋

天气->炎热，夏天，下雨

有人知道吗？我正在做NLP研究。谢谢。

Answer 1

import pandas as pd
# Dictionary of items
d = {'words' : [ [ 'cheap', 'expensive'], ['excited'], ['hot', 'summer'], ['money'], ['rain'] ], 
     'category': ['price', 'entertainment', 'weather', 'price', 'weather']}
# Convert dictionary to dataframe
df = pd.DataFrame(d)
# Unpack the list of 'words' by joining with ','
df.words = df.words.str.join(',')
# Groupby and aggregate to get the unique 'words' for each 'category'
new_df = df.groupby('category').agg({'words':'unique'})
# Since the groupby results in a list of items, unpack by joining with ','
new_df.words = new_df.words.str.join(',')
# reset_index() to convert the groupby object to a dataframe
# This is optional. If not used, 'category' will the index of the dataframe.
new_df.reset_index(inplace=True)
new_df