Pandas DF
Sure, I can help you with pandas! Pandas is a popular Python library for data manipulation and analysis. It provides a DataFrame object, which is a two-dimensional, size-mutable, and heterogeneous tabular data structure.
To get started with pandas, you’ll first need to have it installed. You can install pandas using pip:
pip install pandas
Once pandas is installed, you can import it and create a DataFrame. Here’s a basic example of how to create a pandas DataFrame:
import pandas as pd
# Creating a DataFrame from a dictionary
data = {
‘Name’: [‘Alice’, ‘Bob’, ‘Charlie’, ‘David’],
‘Age’: [25, 30, 22, 27],
‘City’: [‘New York’, ‘San Francisco’, ‘Los Angeles’, ‘Chicago’]
}
df = pd.DataFrame(data)
print(df)
The output will be:
Name Age City
0 Alice 25 New York
1 Bob 30 San Francisco
2 Charlie 22 Los Angeles
3 David 27 Chicago
In this example, we created a DataFrame with three columns: ‘Name’, ‘Age’, and ‘City’. The data for each column is provided in the form of a list in the dictionary. The DataFrame automatically assigns index labels (0, 1, 2, 3) to each row.
You can perform various operations on the DataFrame, such as filtering data, sorting, grouping, and more. Pandas provides a wide range of functionalities to handle data efficiently.
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