<jupyter_start><jupyter_text><jupyter_code># Pandas for managing datasets
import pandas as pd

# Matplotlib for additional customization
from matplotlib import pyplot as plt
%matplotlib inline

# Seaborn for plotting and styling
import seaborn as sns
# Read dataset
df = pd.read_csv('./dutz/dataset/Pokemon.csv', index_col=0)
# Display first 5 observations
df.head()
# Recommended way
sns.lmplot(x='Attack', y='Defense', data=df)
 
# Alternative way
# sns.lmplot(x=df.Attack, y=df.Defense)
# Scatterplot arguments
sns.lmplot(x='Attack', y='Defense', data=df,
           fit_reg=False, # No regression line
           hue='Stage')   # Color by evolution stage<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.11046511627906977, 'fraction_numerical': 0.0029069767441860465, 'mean_word_length': 5.043859649122807, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 0, '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': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '282235', 'license': 'Apache-2.0', 'n_tokens_mistral': 244, 'n_tokens_neox': 236, 'n_words': 63, 'path': 'test/showPo.ipynb', 'repo_name': 'duTianze/machine-learning', 'size': '688'}