In this article, we will explore how to create DataFrames using Pandas, a two-dimensional labeled array that can store data of any data type. We will cover creating DataFrames from lists of tuples and lists of dictionaries, providing step-by-step instructions and code examples for each method.
Key Concepts Explanation
Creating Data Frames from lists
Pandas Data Frame is a two-dimensional labeled array capable of holding attributes of any data type. It is similar to a multi-column Excel spreadsheet or a database table. We can create Data Frames using a list of tuples or a list of dictionaries.
import pandas as pd
sals_ld = [(1, 1500.0), (2, 2000.0, 10.0), (3, 2200.00)]
sals_df = pd.DataFrame(sals_ld)
sals_df
Creating Pandas Data Frame using list of dicts
When creating DataFrames using a list of dictionaries, the column names will be inherited automatically using keys from the dictionary.
sals_ld = [
{'id': 1, 'sal': 1500.0},
{'id': 2, 'sal': 2000.0},
{'id': 3, 'sal': 2200.0}
]
sals_df = pd.DataFrame(sals_ld)
sals_df
Hands-On Tasks
- Create a Pandas Data Frame using a list of tuples with two columns.
- Create another Pandas Data Frame using a list of dictionaries with different keys and values.
Conclusion
In this article, we have covered the basics of creating DataFrames in Pandas using lists of tuples and dictionaries. We encourage you to practice these concepts and engage with the community for further learning.
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