pandas-checks 2.0.1

Non-invasive health checks for Pandas method chains

Pandas Checks

Pandas Checks adds .check methods to Pandas so you can inspect method chains without cutting them up.

As Fleetwood Mac says, you would never break the chain.

import pandas_checks

iris_processed = (
    iris
    .dropna()
    .check.assert_positive(subset=["petal_length", "sepal_length"]) # 🐼🩺 Validate assumptions
    .check.hist('petal_length') # 🐼🩺 Plot the distribution of a column after cleaning

    .query("species=='setosa'")
    .check.head(3)  # 🐼🩺 Display the first few rows after more cleaning
    .check.write("iris_processed.parquet") # 🐼🩺 Export the interim data, with type inferred from name
)

The .check methods didn't modify how iris data got processed. That's the difference between .head() and .check.head().

Table of Contents

💡 See the docs for details and configuration options.

• Installation
• .check methods
  • Assertions
  • Describe data
  • Disable Pandas Checks
  • Export interim files
  • Time your code
  • Visualize data
• Giving feedback and contributing
• License

Installation

# With uv
uv add pandas-checks

# Or with pip
pip install pandas-checks

.check methods

Here's what's in the doctor's bag.

Assertions

General:

• .check.assert_data() - Check that data passes an arbitrary condition, expressed as a lambda function - DataFrame | Series

Type assertions:

• .check.assert_datetime() - DataFrame | Series
• .check.assert_float() - DataFrame | Series
• .check.assert_int() - DataFrame | Series
• .check.assert_str() - DataFrame | Series
• .check.assert_timedelta() - DataFrame | Series
• .check.assert_type() - DataFrame | Series

Value assertions:

• .check.assert_all_nulls() - DataFrame | Series
• .check.assert_less_than() - DataFrame | Series
• .check.assert_greater_than() - DataFrame | Series
• .check.assert_negative() - DataFrame | Series
• .check.assert_no_nulls() - DataFrame | Series
• .check.assert_nrows() - DataFrame | Series
• .check.assert_positive() - DataFrame | Series
• .check.assert_same_nrows() - Confirm that the DataFrame/Series has the same number of rows as that of another DF/Series - DataFrame | Series
• .check.assert_unique() - DataFrame | Series

Describe data

• .check.columns() - DataFrame
• .check.describe() - DataFrame | Series
• .check.dtype() - Series
• .check.dtypes() - DataFrame
• .check.function() - Apply an arbitrary lambda function to your data and see the result - DataFrame | Series
• .check.head() - DataFrame | Series
• .check.info() - DataFrame | Series
• .check.memory_usage() - DataFrame | Series
• .check.ncols() - Count columns - DataFrame | Series
• .check.ndups() - Count rows with duplicate values - DataFrame | Series
• .check.nnulls() - Count rows with null values - DataFrame | Series
• .check.nrows() - Count rows - DataFrame | Series
• .check.nunique() - DataFrame | Series
• .check.print() - Print a string, a variable, or the current dataframe - DataFrame | Series
• .check.shape() - DataFrame | Series
• .check.tail() - DataFrame | Series
• .check.unique() - DataFrame | Series
• .check.value_counts() - DataFrame | Series

Disable Pandas Checks

These methods can disable Pandas Checks methods, temporarily or permanently.

• .check.disable_checks() - Don't run checks. By default, still runs assertions. - DataFrame | Series
• .check.enable_checks() - Run checks again. - DataFrame | Series

Export interim files

• .check.write() - Export the current data, inferring file format from the name - DataFrame | Series

Time your code

• .check.print_time_elapsed(start_time) - Print the execution time since you called start_time = pdc.start_timer() - DataFrame | Series
  
  

💡 Tip: You can use this stopwatch anywhere in your Python code.

from pandas_checks import print_elapsed_time, start_timer

start_time = start_timer()
...
print_elapsed_time(start_time)

Visualize data

• .check.hist() - A histogram - DataFrame | Series
• .check.plot() - An arbitrary plot you can customize - DataFrame | Series

Giving feedback and contributing

If you run into trouble or have questions, I'd love to know. Please open an issue.

Contributions are appreciated! Please see more details.

License

Pandas Checks is licensed under the BSD-3 License.

🐼🩺