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In this conversation, we will explore the Pandas DataFrame.get_value() method. To facilitate our understanding, we will delve into specific examples that illustrate the use of this method. Let’s explore this method further through illustrative examples to gain a deeper understanding of its practical application.
Pandas Dataframe.get_value() Syntax
Syntax:DataFrame.get_value(index, col, takeable=False)
Parameters:
- index : row label
- col : column label
- takeable : interpret the index/col as indexers, default False
Returns : value : scalar value
For link to CSV file Used in Code, click here
What is Pandas Dataframe.get_value() ?
Python stands out as an excellent language for data analysis, thanks in large part to its robust ecosystem of data-centric packages. Among these, Pandas stands out as a powerful tool that simplifies the process of importing and analyzing data. A notable function within the Pandas library is `dataframe.get_value()`, which serves the purpose of swiftly retrieving a single value from the dataframe based on the specified column and index.
get_value() in Pandas Example
Example 1: get_Value method
Use get_value() function to find the value of salary in the 10th row
Python3
# importing pandas as pd
import pandas as pd
# Creating the dataframe
df = pd.read_csv("nba.csv")
# Print the dataframe
df
Output
Python3
# applying get_value() function
df._get_value(10, 'Salary')
Output:
2569260.0
Use get_value() function and pass the column index value rather than name. We can also use integer indexer value of columns by setting the takeable parameter=True.
Python3
# importing pandas as pd
import pandas as pd
# Creating the dataframe
df = pd.read_csv("
nba.csv "
)
# column index value of "Name" column is 0
# We have set takeable = True
# to interpret the index / col as indexer
df.get_value(4, 0, takeable=True)
Output:
Jonas Jerebko
Pandas get_value() Without Dataset
In this example, we show the application of the deprecated dataframe.get_value() function in Python with a simple Pandas dataframe. The code showcases how to retrieve specific values from the dataframe, providing insights into the age of an individual named ‘Bob’. Note that while dataframe.get_value() is deprecated, this example serves as an illustration of its usage for educational purposes
Python3
import pandas as pd
# Creating a simple dataframe
data = {
'Name': ['Alice', 'Bob', 'Charlie'],
'Age': [25, 30, 22],
'Salary': [50000, 60000, 45000]
}
df = pd.DataFrame(data)
df.set_index('Name', inplace=True)
# Displaying the dataframe
print("Original DataFrame:")
print(df)
# Using dataframe.get_value() to retrieve a specific value
selected_age = df.get_value('Bob', 'Age')
# Displaying the result
print("\nUsing get_value() to get Bob's age:")
print(f"Bob's Age: {selected_age}")
Output
Original DataFrame:
Age Salary
Name
Alice 25 50000
Bob 30 60000
Charlie 22 45000
Using get_value() to get Bob's age:
Bob's Age: 30
Last Updated : 01 Feb, 2024
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