<jupyter_start><jupyter_text>Exercise 4: Creating Line Graphs Using Different Libraries<jupyter_code>%matplotlib inline
import numpy as np
X = np.arange(0,100)
Y = np.random.randint(0,200, size=X.shape[0])
import matplotlib.pyplot as plt
plt.plot(X, Y)

import pandas as pd
df = pd.DataFrame({'x':X, 'y_col':Y})

plt.plot('x', 'y_col', data=df)
df.plot('x', 'y_col')
import seaborn as sns
sns.lineplot(X, Y)
sns.lineplot('x', 'y_col', data=df)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1649048625792812, 'fraction_numerical': 0.021141649048625793, 'mean_word_length': 6.770491803278689, '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': '644934', 'license': 'MIT', 'n_tokens_mistral': 211, 'n_tokens_neox': 202, 'n_words': 45, 'path': 'Lesson02/Exercise04.ipynb', 'repo_name': 'bsitati/Big-Data-Analysis-with-Python', 'size': '473'}