In this post you will learn how to use in and not in in pandas to filter data.
Method 1 –
Read a dataset to work with
import pandas as pd
url = "https://raw.githubusercontent.com/bprasad26/lwd/master/data/clothing_store_sales.csv"
df = pd.read_csv(url)
df = df.head()
let’s say that you want to select only rows where the Method of Payment is Discover or MasterCard.
To do that you can use pandas isin() method
cards_to_keep = ["Discover","MasterCard"]
df[df['Method of Payment'].isin(cards_to_keep)]
And if you want to implement not in in pandas, then just use the tilda (~) sign like this
df[~df['Method of Payment'].isin(cards_to_keep)]
Method 2 –
To implement in and not in in pandas, you can also use pandas query method.
# need to rename the column first
# as it contains spaces between words
df.rename(columns={"Method of Payment":"Method_of_Payment"}, inplace=True)df.query("Method_of_Payment in @cards_to_keep")
And for not in
df.query("Method_of_Payment not in @cards_to_keep")