计算两个数据帧之间的 pandas 集差异
问题描述：
想知道如何使用两个不同的数据帧来计算Python熊猫中的集合差异.
Wondering how to compute set difference in Python's Pandas using two different dataframes.
一个数据帧(df1)的格式为:
One dataframe (df1) is of the format:
State City Population
NY Albany 856654
WV Wheeling 23434
SC Charleston 35323
OH Columbus 343534
WV Charleston 34523
第二个数据帧(df2)是
And the second data frame (df2) is
State City
WV Wheeling
OH Columns
我需要一个返回以下数据帧的操作
And I need an operation that returns the following data frame
State City Population
NY Albany 856654
SC Charleston 35323
WV Charleston 34523
从本质上讲，我无法弄清楚如何基于2列从df1中减去" df2(两者都是必需的，因为我将在不同州使用重复的城市名称).
Essentially, I can't figure out how to "subtract" df2 from df1 based on the 2 columns (need both since I'll have repeats of city names across different states).
答
使用indicator进行左联接，该联接提供有关每一行的原点的信息，然后您可以根据indicator进行过滤:
Do a left join with indicator which gives information on the origin of each row, then you can filter based on the indicator:
df1.merge(df2, indicator=True, how="left")[lambda x: x._merge=='left_only'].drop('_merge',1)
#State City Population
#0 NY Albany 856654
#2 SC Charleston 35323
#4 WV Charleston 34523