Is there a good pythonic way to filter dataframe with multiple conditions?

Question

Looking for an efficient way to do multi-condition filter (better not iterating through each row).

Original Data:

fruit      price  qty   comment
apple       1.5   10    In Stock
apple       0.7   20    In Stock
pear        3.0   5     In Stock
pear        2.0   5     In Stock 
pear        1.2   30    Out Stock

Filer logic:

if fruit = 'apple'  keep price = 1.5
if fruit = 'Pear'   keep qty = 5

expected output:

fruit      price  qty   comment
apple       1.5   10    In Stock
pear        3.0   5     In Stock
pear        2.0   5     In Stock

So `df[((df["fruit"]=="apple")&(df["price"]==1.5))|((df["fruit"]=="pear")&(df["qty"]==5))]`? — pault, Sep 13 '19 at 18:43
Possible duplicate of [Selecting with complex criteria from pandas.DataFrame](https://stackoverflow.com/questions/15315452/selecting-with-complex-criteria-from-pandas-dataframe) — pault, Sep 13 '19 at 18:44

score 1 · Accepted Answer · answered Sep 13 '19 at 18:45

You need to create boolean masks with & and then need '|' for both mask merging.

m1 = ((df['fruit']=='apple') & (df['price']==1.5))
m2 = ((df['fruit']=='pear') & (df['qty']==5))
df.loc[m1 | m2]

Output:

   fruit    price   qty comment
0   apple   1.5 10  In Stock
2   pear    3.0 5   In Stock
3   pear    2.0 5   In Stock

Is there a good pythonic way to filter dataframe with multiple conditions?

1 Answers1