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: 钱 -> 价格

r5: 下雨 -> 天气

---

那么我想以这种模式显示它：

价格 -> 便宜，昂贵，金钱

娱乐 -> 兴奋

天气 -> 炎热，夏天，下雨

有人知道吗？我正在做 NLP 研究。谢谢你。

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