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import pandas as pd
pd.DataFrame({'a': [1,2,3], 'b': [0,0,0], 'c': ['One', 'Two', 'Three']})

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# %hide-cell
print("This cell won't make it to the final document")

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# %hide-output
print("This code will be shown, but it's output won't")

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# %hide-source
print("This code won't be shown, but it's output will")

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import seaborn as sns
x = np.arange(0, 10, 0.1)
y = np.sin(x)
sns.scatterplot(x = y,y = x);

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import numpy as np
import matplotlib.pyplot as plt
x = np.arange(0, 10, 0.1)
y = np.sin(x)
plt.plot(x,y);

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from nb2medium.upload import nb2medium

nb2medium(title = 'My First Article', notebook = 'path/to/notebook.ipynb');

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fig['layout'] = go.Layout(
  font = {'size' : 14},
  plot_bgcolor = 'white',
  xaxis = {'showline': True,
           'visible': True,
           'range': (0, data['Value'].max()),
           'title_text': 'Production Quantity (tonnes)' # title of the x axis
          },
  yaxis = {'showline': False, 
          'visible': True, # to show the title

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#1 Assign color to each unique item
from random import sample

colors = {item: 'rgb({}, {}, {})'.format(*sample(range(256), 3)) for item in data['Item'].unique()}
data['color'] = data['Item'].map(colors)

#2 Slice data, select earliest date available

##2.1 Select earliest year available 
frame1 = data[data['Year'] == data['Year'].min()]