Create a Pandas DataFrame from Lists



In this guide, we will learn how to create a Pandas DataFrame from lists. Pandas is a powerful library for data manipulation and analysis in Python, and it provides a convenient way to work with tabular data using DataFrames.

Creating a DataFrame

To create a DataFrame from lists, we can use the pd.DataFrame() function provided by the Pandas library. This function takes a dictionary as an argument, where the keys represent column names and the values represent the corresponding lists of data.

Let’s take a look at an example:

import pandas as pd
Create lists of data

names = ['Alice', 'Bob', 'Charlie', 'Dave']
ages = [25, 30, 35, 40]
cities = ['New York', 'Los Angeles', 'Chicago', 'Houston']
Create a dictionary from the lists

data = {'Name': names, 'Age': ages, 'City': cities}
Create a DataFrame from the dictionary

df = pd.DataFrame(data)
Print the DataFrame

print(df)
   Name  Age         City
0  Alice   25     New York
1    Bob   30  Los Angeles
2   Charlie 35     Chicago
3    Dave  40     Houston

As you can see, we first created three separate lists for the names, ages, and cities. Then, we created a dictionary called data with the keys ‘Name’, ‘Age’, and ‘City’ corresponding to the column names. Finally, we passed the data dictionary to the pd.DataFrame() function to create the DataFrame.

Method 2: Using a dictionary

A dictionary is another data structure that can be used to create a DataFrame. In this case, the keys of the dictionary will be the column names of the DataFrame, and the values will be the lists that represent the data in each column.

import pandas as pd

data = {'Name': ['Alice', 'Bob', 'Charlie', 'David'],
'Age': [25, 30, 35, 40],
'Salary': [50000, 60000, 70000, 80000]}

df = pd.DataFrame(data)
print(df)

Output:


       Name  Age  Salary
0     Alice   25   50000
1       Bob   30   60000
2   Charlie   35   70000
3     David   40   80000

In this example, we define a dictionary with three keys (Name, Age, and Salary), and the corresponding values are lists that contain the data for each column. We then pass this dictionary to the DataFrame constructor to create the DataFrame.

Method 3: Using a list of dictionaries

Another way to create a DataFrame is to use a list of dictionaries. Each dictionary in the list represents a row in the DataFrame, and the keys of the dictionaries correspond to the column names.

import pandas as pd

data = [{'Name': 'Alice', 'Age': 25, 'Salary': 50000},
{'Name': 'Bob', 'Age': 30, 'Salary': 60000},
{'Name': 'Charlie', 'Age': 35, 'Salary': 70000},
{'Name': 'David', 'Age': 40, 'Salary': 80000}]

df = pd.DataFrame(data)
print(df)

Output:


       Name  Age  Salary
0     Alice   25   50000
1       Bob   30   60000
2   Charlie   35   70000
3     David   40   80000

In this example, we define a list of dictionaries, where each dictionary represents a row in the DataFrame. We then pass this list to the DataFrame constructor to create the DataFrame.

Last Updated on May 17, 2023 by admin

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