df-compress 0.6.3

A python package to compress pandas DataFrames akin to Stata's `compress` command

df-compress

A python package to compress pandas DataFrames akin to Stata's compress command. This function may prove particularly helpfull to those dealing with large datasets.

Installation

You can install df-compress by running the following command:

pip install df_compress

How to use

After installing the package use the following import:

from df_compress import compress

Example

It follows a reproducible example on df-compress usage:

from df_compress import compress
import pandas as pd
import numpy as np

df = pd.DataFrame(columns=["Year","State","Value","Int_value"])
df.Year = np.random.randint(low=2000,high=2023,size=200).astype(str)
df.State = np.random.choice(['RJ','SP','ES','MT'],size=200)
df.Value= np.random.rand(200,1)
df.Int_value = df.Value*10 // 1

compress(df, show_conversions=True) # which modifies the original DataFrame without needing to reassign it

Which will print for you the transformations and memory saved:

Initial memory usage: 0.02 MB
Final memory usage: 0.00 MB
Memory reduced by: 0.02 MB (91.3%)

Variable type conversions:
   column    from       to  memory saved (MB)
     Year  object    int16           0.009727
    State  object category           0.009178
    Value float64  float32           0.000763
Int_value float64     int8           0.001335

Optional Parameters

The function has three optimal parameters (arguments):

• convert_strings (bool): Whether to attempt to parse object columns as numbers
  • defaults to True
• numeric_threshold (float): Indicates the proportion of valid numeric entries needed to convert a string to numeric
  • defaults to 0.999
• show_conversions (bool): whether to report the changes made column by column
  • defaults to False