根据列中的最大值过滤 Pandas Dataframe
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Filter pandas Dataframe based on max values in a column
提问by wrcobb
I have a DataFrame with repeating values in the index. I would like to filter this dataset down to only show me one instance of each index by selecting the row within the index with the greatest value in a different column. For example, my DataFrame looks like this:
我有一个在索引中包含重复值的 DataFrame。我想通过选择索引中不同列中具有最大值的行来过滤此数据集，以仅显示每个索引的一个实例。例如，我的 DataFrame 如下所示：
df:
df：
Product ID Store Sales
1 A 50
1 B 200
1 C 20
2 A 400
2 B 10
3 A 200
4 A 50
4 B 100
4 C 500
I would like to filter this data down to this:
我想将此数据过滤为：
df2:
df2：
Product ID Store Sales
1 B 200
2 A 400
3 A 200
4 C 500
Any thoughts on how best to approach this issue in pandas?
关于如何最好地在大Pandas中解决这个问题的任何想法？
Thanks very much for your time -
非常感谢你花时间陪伴 -
回答by EdChum
You can perform a groupbyon 'Product ID', then apply idxmaxon 'Sales' column.
This will create a series with the index of the highest values.
We can then use the index values to index into the original dataframe using iloc
您可以groupby在“产品 ID”上执行，然后idxmax在“销售”列上应用。这将创建一个具有最高值索引的系列。然后我们可以使用索引值索引到原始数据帧中iloc
In [201]:
df.iloc[df.groupby('Product ID')['Sales'].agg(pd.Series.idxmax)]
Out[201]:
Product_ID Store Sales
1 1 B 200
3 2 A 400
5 3 A 200
8 4 C 500
