<jupyter_start><jupyter_text>Feature Engineering Examples [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/slickml/slick-ml/blob/master/examples/feature_engineering.ipynb)  Google Colab Configuration<jupyter_code>!git clone https://github.com/slickml/slick-ml.git
%cd slick-ml
!pip install -r requirements.txt<jupyter_output><empty_output><jupyter_text>Local Environment Configuration<jupyter_code># Change path to project root
%cd ..<jupyter_output><empty_output><jupyter_text>Import Python Libraries<jupyter_code>%load_ext autoreload

# widen the screen
from IPython.core.display import display, HTML
display(HTML("<style>.container { width:95% !important; }</style>"))

# change the path and loading class
import os, sys
import pandas as pd
import numpy as np
import seaborn as sns
%autoreload
from slickml.feature_engineering import noisy_features<jupyter_output><empty_output><jupyter_text>______ Noisy Features  Example 1: Numpy Array<jupyter_code>X = np.random.rand(4,3)
X
noisy_features(X)<jupyter_output><empty_output><jupyter_text>Example 2: Pandas DataFrame<jupyter_code>X = pd.DataFrame(np.random.rand(4,3),
                 columns=[F"col_{i}" for i in range(X.shape[1])])
X
noisy_features(X)<jupyter_output><empty_output><jupyter_text>Example 3: List<jupyter_code>X = [[1, 2, 3],
     [4, 5, 6],
     [7, 8, 9]]
X
noisy_features(X)
a = 1.
isinstance(a, float)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.12771739130434784, 'fraction_numerical': 0.01358695652173913, 'mean_word_length': 6.7936507936507935, 'pattern_counts': {'":': 0, '<': 27, '<?xml version=': 0, '>': 27, 'https://': 3, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '6', 'dir': 'jupyter-structured-clean-dedup', 'id': '58533', 'license': 'MIT', 'n_tokens_mistral': 556, 'n_tokens_neox': 530, 'n_words': 104, 'path': 'examples/feature_engineering.ipynb', 'repo_name': 'Mark-S-Bartlett/slick-ml', 'size': '1472'}