Exporting data

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Exporting data#

from perse import DataFrame
import numpy as np

# Generate sample data
np.random.seed(42)
data = {
    "A": np.random.randint(0, 100, 10),
    "B": np.random.random(10),
    "C": np.random.choice(["X", "Y", "Z"], 10),
}

df = DataFrame(data)

# Export as CSV file
df.to_csv('example.csv')

# Export as Excel file
df.to_excel('example.xlsx')

# Export as JSON file
df.to_json('example.json')


# Alternatively this concise expression can also be used
df > 'example.csv'
df > 'example.xlsx'
df > 'example.json'

Pipe Operator#

In Python, the | operator is traditionally used as the OR operator. However, in the DataFrame class, the | operator has been repurposed for a functional, chainable approach, similar to other modern data processing libraries. This enables more readable and flexible expressions.

# Applying the print function to the DataFrame instance
df | print

# Chaining functions: the instance is returned if no modification is made
df2 = df | print | print

# Using a lambda function to call `to_csv` with arguments, demonstrating flexibility in piping
_ = df | (lambda x: x.to_csv('example.csv'))
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