<jupyter_start><jupyter_text>Test<jupyter_code>!pip install plotly cufflinks
# from https://stackabuse.com/using-plotly-library-for-interactive-data-visualization-in-python/
import pandas as pd
import numpy as np
%matplotlib inline

from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot

init_notebook_mode(connected=True)

import cufflinks as cf
cf.go_offline()

8 * 24
# from https://stackabuse.com/using-plotly-library-for-interactive-data-visualization-in-python/
import seaborn as sns
dataset = sns.load_dataset('tips')
dataset.head()

dataset2 = dataset[["total_bill", "tip", "size"]]
dataset2.plot()

dataset2.iplot()

dataset.iplot(kind='bar', x=['time', 'sex'],y='total_bill')
dataset.mean().iplot(kind='bar')
dataset.mean().iplot(kind='barh')
dataset.iplot(kind='scatter', x='total_bill', y='tip', mode='markers',
              title='Scatter plot', xTitle='Bill ($)', yTitle='Tip ($)')
dataset.iplot(kind='scatter', x='total_bill', y='tip', mode='markers',
             # log y axis
             layout=dict(xaxis=dict(title='Bill ($)'),
                         yaxis=dict(type='log',
                                    title='Tip ($)'),
                         title='Scatter plot'))
dataset2.iplot(kind='box')
dataset2.scatter_matrix()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1632183908045977, 'fraction_numerical': 0.006130268199233717, 'mean_word_length': 4.081712062256809, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 2, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 2, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '5761', 'license': 'MIT', 'n_tokens_mistral': 451, 'n_tokens_neox': 435, 'n_words': 73, 'path': 'tests/j_notebooks/plotly iplot examples.ipynb', 'repo_name': 'KarrLab/wc_sim', 'size': '1305'}