This article will discuss different ways to get the first value a column in a Pandas Dataframe. In all the solutions, we will first select the Column by either column name or index position; then, we will see different techniques to get and set the first value of that Column.
Table of Contents
- Get the first value of a column based on the column name
- Get the first value of a column based on column index position.
A DataFrame is a data structure offered by the Pandas module in Python. It stores the data in tabular format, i.e., in rows and columns. Let’s create a DataFrame from a list of tuples,
import pandas as pd # List of Tuples students = [('jack', 34, 'Sydney', 'Australia', 0), ('Riti', 30, 'Delhi', 'India', 0), ('Vikas', 31, 'Mumbai', 'India', 0), ('Neelu', 32, 'Bangalore','India', 0), ('John', 16, 'New York', 'US', 0), ('Mike', 17, 'las vegas', 'US', 0)] # Create a DataFrame object df = pd.DataFrame( students, columns=['Name', 'Age', 'City', 'Country', 'Budget'], index=['a', 'b', 'c', 'd', 'e', 'f']) print(df)
Output
Name Age City Country Budget a jack 34 Sydney Australia 0 b Riti 30 Delhi India 0 c Vikas 31 Mumbai India 0 d Neelu 32 Bangalore India 0 e John 16 New York US 0 f Mike 17 las vegas US 0
Now let’s see how to get the first value of a specific column of this DataFrame,
Get the first value of a column based on the column name
Suppose we know the column name and want to fetch the first value of that Column. We can do that using two techniques. Let’s see them one by one,
Get the first value of a column using iat[]
Select the Column of the DataFrame as a Series object, based on the column name. Then call the iat[0] attribute on that Series object to get the first value of that Column. For example,
# Get first value of column 'City' first_value = df['City'].iat[0] print(first_value)
Output:
Sydney
Here we fetched the first value of the column ‘City’ from the DataFrame. The iat[0] returns the reference of the first value of the Series. We can use this to change the first value of the Column too. For example,
# Change the First value of column 'City' df['City'].iat[0] = 'Mumbai' # Display the DataFrame print(df)
Output:
Name Age City Country Budget a jack 34 Mumbai Australia 0 b Riti 30 Delhi India 0 c Vikas 31 Mumbai India 0 d Neelu 32 Bangalore India 0 e John 16 New York US 0 f Mike 17 las vegas US 0
Here, we changed the first value of column ‘City’ to Mumbai.
Get the first value of a column using iloc[]
In Pandas, the DataFrame provides a property iloc[]. In the iloc[row_number, column_number], we need to pass the row and column index positions, and it fetches the cell value based on that. But we have the column name instead of the column index position. So we need to get the column index from the column name and then use the iloc[] property with row value 0 to get the first value of the Column. For example,
import pandas as pd # List of Tuples students = [('jack', 34, 'Sydney', 'Australia', 0), ('Riti', 30, 'Delhi', 'India', 0), ('Vikas', 31, 'Mumbai', 'India', 0), ('Neelu', 32, 'Bangalore','India', 0), ('John', 16, 'New York', 'US', 0), ('Mike', 17, 'las vegas', 'US', 0)] # Create a DataFrame object df = pd.DataFrame( students, columns=['Name', 'Age', 'City', 'Country', 'Budget'], index=['a', 'b', 'c', 'd', 'e', 'f']) print(df) # Get first value of column 'City' first_value = df.iloc[0, df.columns.get_loc('City')] print(first_value)
Output:
Name Age City Country Budget a jack 34 Sydney Australia 0 b Riti 30 Delhi India 0 c Vikas 31 Mumbai India 0 d Neelu 32 Bangalore India 0 e John 16 New York US 0 f Mike 17 las vegas US 0 Sydney
Here we fetched the first value of the column ‘City’ from the DataFrame.
Using the get_loc() function, we first fetched the column number from column name and then using passed that to iloc[] property of the DataFrame with row value 0. The iloc[], returned the reference of the first value of the Column. We can use this to change the first value of the Column too. For example,
# Change the First value of column 'City' df.iloc[0, df.columns.get_loc('City')] = 'Tokyo' # Display the DataFrame print(df)
Output:
Name Age City Country Budget a jack 34 Tokyo Australia 0 b Riti 30 Delhi India 0 c Vikas 31 Mumbai India 0 d Neelu 32 Bangalore India 0 e John 16 New York US 0 f Mike 17 las vegas US 0
Here, we changed the first value of column ‘City’ to Tokyo.
Get the first value of a column based on column index position
In Pandas, the DataFrame provides a property iloc[]. In the iloc[row_number, column_number], we need to pass the row and column index positions, and it fetches the cell value based on that.
As we already have the column index position, we can directly use that and pass 0 as the row number to get the first value of the Column. For example,
import pandas as pd # List of Tuples students = [('jack', 34, 'Sydney', 'Australia', 0), ('Riti', 30, 'Delhi', 'India', 0), ('Vikas', 31, 'Mumbai', 'India', 0), ('Neelu', 32, 'Bangalore','India', 0), ('John', 16, 'New York', 'US', 0), ('Mike', 17, 'las vegas', 'US', 0)] # Create a DataFrame object df = pd.DataFrame( students, columns=['Name', 'Age', 'City', 'Country', 'Budget'], index=['a', 'b', 'c', 'd', 'e', 'f']) print(df) column_index = 2 # Get first value of column index 2 first_value = df.iloc[0, column_index] print(first_value)
Output:
Name Age City Country Budget a jack 34 Sydney Australia 0 b Riti 30 Delhi India 0 c Vikas 31 Mumbai India 0 d Neelu 32 Bangalore India 0 e John 16 New York US 0 f Mike 17 las vegas US 0 Sydney
Here we fetched the first value of the column ‘City’ from the DataFrame. The iloc[] returns the reference of the first value of the Column. We can use this to change the first value of the Column too. For example,
column_index = 2 # Change the First value of column index 2 df.iloc[0, column_index] = 'Yokohama' # Display the DataFrame print(df)
Output:
Name Age City Country Budget a jack 34 Yokohama Australia 0 b Riti 30 Delhi India 0 c Vikas 31 Mumbai India 0 d Neelu 32 Bangalore India 0 e John 16 New York US 0 f Mike 17 las vegas US 0
Here, we changed the first value of column ‘City’ to Yokohama.
Summary
We learned about different ways to get and set a column’s first value, either by column name or index position.
Pandas Tutorials -Learn Data Analysis with Python
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Pandas Tutorial Part #1 - Introduction to Data Analysis with Python
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Pandas Tutorial Part #2 - Basics of Pandas Series
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Pandas Tutorial Part #3 - Get & Set Series values
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Pandas Tutorial Part #4 - Attributes & methods of Pandas Series
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Pandas Tutorial Part #5 - Add or Remove Pandas Series elements
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Pandas Tutorial Part #6 - Introduction to DataFrame
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Pandas Tutorial Part #7 - DataFrame.loc[] - Select Rows / Columns by Indexing
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Pandas Tutorial Part #8 - DataFrame.iloc[] - Select Rows / Columns by Label Names
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Pandas Tutorial Part #9 - Filter DataFrame Rows
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Pandas Tutorial Part #10 - Add/Remove DataFrame Rows & Columns
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Pandas Tutorial Part #11 - DataFrame attributes & methods
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Pandas Tutorial Part #12 - Handling Missing Data or NaN values
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Pandas Tutorial Part #13 - Iterate over Rows & Columns of DataFrame
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Pandas Tutorial Part #14 - Sorting DataFrame by Rows or Columns
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Pandas Tutorial Part #15 - Merging or Concatenating DataFrames
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Pandas Tutorial Part #16 - DataFrame GroupBy explained with examples
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