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A simple implementation of dataframe functionality

Project description

IE Pandas

This is Team C's final project in Advanced Python.

A simple implementation of dataframe functionality

The library is available in Pypi


The easiest way to install ie_pandas is through pip

pip install ie_pandas

To use it in your project, you must first import the library

from ie_pandas import Dataframe

You can create a frame by the following 4 methods:

  • A list of lists
  • A numpy array of lists
  • A dictionary of lists with keys being column names and values being the values for that column
  • A dictionary of numpy arrays (same as with lists)
dictionary = {'c0': [1, 3, 5], 'c1': [7, 6, 2], 'c2': [2, 4, 7], 'c3': [5, 3, 9]}
df = DataFrame(dictionary)


  • Create dataframes from list of lists, numpy arrays, dictionaries of lists and numpy arrays
dictionary = {'c0': [1, 3, 5], 'c1': [7, 6, 2], 'c2': [2, 4, 7], 'c3': [5, 3, 9]}
df = DataFrame(dictionary)

# You may optionally pass along two parameters, cols and index
# cols determines the column names (if blank they will be numerical strings)
# index determines the row names (if blank they will be numbers)
df = DataFrame(dictionary, cols = ["col0", "col1", "col2", "col3"], index = ["row1", "row2", "row3"])
  • Access columns by name
  • Access rows by position or by row name
# or
  • Access data like a numpy array by name
df[0:2, 1:3]
  • Modify dataframe
df[0,0] = 3
  • Sum, median, mean, min, max methods (only work for numerical columns)

Since the underlying object of the dataframe is a numpy array, you may perform aditional functionality like

df[:, 1:2].sum()
  • Visualize relationships between 2 entirely numerical columns (only for numerical columns)
df.visualize(df[:, 2], df[:, 3])
# or
df.visualize(df["c1"], df["c2"])


IE_Pandas only requires the following packages:

  • Numpy (>=1.16)
  • Matplotlib (>=3.0.2)

However, for development purposes, the following packages are needed:

  • Pytest (>= 4.2)
  • Pytest-cov (>= 2.6)
  • Black (for PEP8 compliance)


For development purposes, you may download the files directly and install the library locally by placing your terminal in the downloaded folder and doing

pip install --editable .[dev]

Then, to execute the tests you just need to run

pytest --cov

IE_Pandas Coding Style

IE_Pandas complies to PEP8 and uses black for coding standards


SemVer is used for versioning.


This project is licensed under the MIT License - see the License file for details

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