I have the following dataframe:
我有以下数据帧:
symbol, name
abc Jumping Jack
xyz Singing Sue
rth Fat Frog
I then have another dataframe with the same structure (symbol + name). I need to output all the symbols which are in the first dataframe but not the second.
然后我有另一个具有相同结构的数据帧(符号+名称)。我需要输出第一个数据帧中的所有符号,但不输出第二个数据帧中的所有符号。
The name column is allowed to differ. For example I could have symbol = xyz in both dataframes but with different names. That is fine. I am simply trying to get the symbols which do not appear in both dataframes.
名称列允许不同。例如,我可以在两个数据帧中使用symbol = xyz但名称不同。那样就好。我只是想获得两个数据帧中都没有出现的符号。
I am sure this can be done using pandas merge and then outputting the rows that didn't merge, but I just can't seem to get it right.
我确信这可以使用pandas merge完成,然后输出没有合并的行,但我似乎无法正确使用它。
1 个解决方案
#1
2
Use isin and negate the condition using ~:
使用isin并使用〜来否定条件:
df[~df['symbol'].isin(df1['symbol'])]
This will return rows where 'symbol' is present in your first df and not in the other df
这将返回第一个df中存在“symbol”但不存在于另一个df中的行
#1
2
Use isin and negate the condition using ~:
使用isin并使用〜来否定条件:
df[~df['symbol'].isin(df1['symbol'])]
This will return rows where 'symbol' is present in your first df and not in the other df
这将返回第一个df中存在“symbol”但不存在于另一个df中的行