In this article, we will see how to search a value within Pandas DataFrame row in Python.
Importing Libraries and Data
Here we are going to import the required module and then read the data file as dataframe.
The link to dataset used is here
Python3
# importing pandas as ps import pandas as pd # importing data using .read_csv() method df = pd.read_csv( "data.csv" ) |
Output:
Searching a Value
Here we will search the column name with in the dataframe.
Syntax : df[df[‘column_name’] == value_you_are_looking_for]
where df is our dataFrame
We will search all rows which have a value “Yes” in purchased column.
Python3
df[df[ "Purchased" ] = = "Yes" ] # This line of code will print all rows # which satisfy the condition df["Purchased"] == "Yes" # In other words df["Purchased"] == "Yes" # will return a boolean either true or false. # if it returns true then we will print that # row otherwise we will not print the row. |
Output:
We can also use more than one condition to search a value. Lets see a example to find all rows which have Age value between 35 and 40 inclusive.
Syntax : df[condition]
where df is our dataFrame
Python3
df[(df[ "Age" ] > = 35 ) & (df[ "Age" ] < = 40 )] # This line of code will return all # rows which satisfies both the conditions # ie value of age >= 35 and value of age <= 40 |
Output: