<jupyter_start><jupyter_text>Jupyter 101After this tutorial, you will learn how to manipulate and represent data with jupyter and python. You can clone the tutorial by the following command.```shgit clone  <EMAIL>:g0vhk-io/sitcon-hk-2017-jupyter-tutorial.git``` What is jupyter Simple Mark Down<jupyter_code>from IPython.display import YouTubeVideo
YouTubeVideo('oHg5SJYRHA0')
%%HTML
<h1>Hello World</h1>
<pre>
int main() {
    return 0;
}
</pre>
!pip freeze
import plotly
import pandas as pd


df = pd.read_csv('water.csv')
del df['Remarks']
df[df['Year']>2010]<jupyter_output><empty_output><jupyter_text>Water Quantity<jupyter_code>import plotly.plotly as py
import plotly.graph_objs as go

quantities = go.Scatter(
    x = df['Year'],
    y = df['quantity'],
    name = 'quantity'
)

expenditures = go.Scatter(
    x = df['Year'],
    y = df['expenditure'],
    name = 'expenditure'
)

data = [quantities, expenditures]
plotly.tools.set_credentials_file(username='g0vhkio', api_key='EExyKfq9fHDaO8Or7NXL')

py.iplot(data, filename='basic-line', title='Water')<jupyter_output>High five! You successfully sent some data to your account on plotly. View your plot in your browser at https://plot.ly/~g0vhkio/0 or inside your plot.ly account where it is named 'basic-line'
{'fraction_non_alphanumeric': 0.12283464566929134, 'fraction_numerical': 0.01811023622047244, 'mean_word_length': 5.355, 'pattern_counts': {'":': 0, '<': 13, '<?xml version=': 0, '>': 14, 'https://': 1, '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': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '331789', 'license': 'Apache-2.0', 'n_tokens_mistral': 487, 'n_tokens_neox': 455, 'n_words': 121, 'path': 'Jupyter 101.ipynb', 'repo_name': 'g0vhk-io/sitcon-hk-2017-jupyter-tutorial', 'size': '1277'}