How To Create A Dataframe In Python

In this tutorial, we will learn how to create a dataframe in Python using the widely popular library, Pandas.

Dataframes are essential in data manipulation and analysis, as they help you organize, store, and handle complex datasets in a tabular format. By following this guide, you will be comfortable in creating and manipulating dataframes to suit your project’s needs.

Step 1: Install Pandas library

First, make sure you have the Pandas library installed in your Python environment. If you haven’t installed it yet, you can do this by running the following command:

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!pip install pandas

Step 2: Import Pandas

Next, import the Pandas library in your Python script. This is usually done at the beginning of your code.

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import pandas as pd

In this example, we import pandas using the alias pd. This is a common practice when working with Pandas, so you will see it frequently throughout this tutorial.

Step 3: Create a dictionary with key-value pairs

Now, create a dictionary that represents your data. Your dictionary’s keys should represent the column names of your dataframe, and the values should be lists containing the individual data points corresponding to each column.

For this tutorial, we will create a simple dataset containing information about fruits.

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data = {'Fruit': ['Apple', 'Orange', 'Banana', 'Grape'],<br>'Color': ['Red', 'Orange', 'Yellow', 'Purple'],<br>'Weight': [1.2, 0.3, 0.11, 0.05]}

Step 4: Create a dataframe from the dictionary

You can now create a dataframe using the pd.DataFrame() function and passing the dictionary as an argument. Here’s how it’s done:

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df = pd.DataFrame(data)

Full code

Now, you can use the power of Pandas to manipulate this dataframe as needed. Below is the complete code for your reference:

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import pandas as pd
 
data = {'Fruit': ['Apple', 'Orange', 'Banana', 'Grape'],
        'Color': ['Red', 'Orange', 'Yellow', 'Purple'],
        'Weight': [1.2, 0.3, 0.11, 0.05]}
 
df = pd.DataFrame(data)
 
print(df)

Output

    Fruit     Color   Weight
0   Apple      Red      1.20
1  Orange   Orange     0.30
2  Banana  Yellow      0.11
3   Grape  Purple      0.05

Conclusion

Creating a dataframe in Python with Pandas is fairly straightforward. By following the steps in this tutorial, you should now have a basic understanding of dataframe creation, which is essential for data manipulation and analysis.

Pandas offers a plethora of functionalities for working with dataframes, so explore further to get the most out of this powerful library!