war*_*m06 5 python group-by python-3.x pandas
我是 Stack Overflow 的新手,因此也欢迎任何社区最佳实践。
#aggregate rides and average of fares
combo_grouped_df =combo_df.groupby(['city','type'])
#combo_grouped_df.set_index('city') does not work!
combo_grouped_df.head()
avg_fare =combo_grouped_df['fare'].mean()
total_rides =combo_grouped_df['ride_id'].count()
city_type = combo_grouped_df['type']
summary_df = pd.DataFrame({"Average Fare": avg_fare,
"Number of Rides": total_rides,
"Type": combo_grouped_df['type']}) # how to get type in this dict?????
summary_df.head()}
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结果是:
Average Fare Number of Rides \
city type
Amandaburgh Urban 24.641667 18
Barajasview Urban 25.332273 22
Barronchester Suburban 36.422500 16
Bethanyland Suburban 32.956111 18
Bradshawfurt Rural 40.064000 10
Type
city type
Amandaburgh Urban ((Amandaburgh, Urban), [Urban, Urban, Urban, U...
Barajasview Urban ((Barajasview, Urban), [Urban, Urban, Urban, U...
Barronchester Suburban ((Barronchester, Suburban), [Suburban, Suburba...
Bethanyland Suburban ((Bethanyland, Suburban), [Suburban, Suburban,...
Bradshawfurt Rural ((Bradshawfurt, Rural), [Rural, Rural, Rural, ...
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我想将 goupby 'type' 索引移动到 'Type' 所在的列。或者让 'Type' 显示为没有括号的单个字符串(例如 'Urban')。
df.set_index = False
不起作用,因为我想保留“城市”索引。groupby 的 groupby 似乎也不起作用。任何帮助,将不胜感激。
为清楚起见进行编辑:我希望对“城市”进行分组并将其用作索引。我想在数据框中而不是在索引中有“类型”。当前,'Type' 返回一个值列表,这些值本质上是相同的重复值。
所有你需要的是:
import pandas as pd
# Group it
group_df = combo_df.groupby(['city','type'])
# Aggregate it
aggregated_df = group_df.agg({'fare': 'mean', 'ride_id': 'count'})
# Reset index (only type)
summary_df = aggregated_df.reset_index(level=1)
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