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Working offline with pycharm (no notebook)

I using pycharm community version with Python 36 on windows 10
i didn’t succeeded in understanding the logic of the plotly offline and i am failing to create a chart in the following code. i will appreciate very much your assistant.

the code is taken from here https://blog.patricktriest.com/analyzing-cryptocurrencies-python/

import os
import numpy as np
import pandas as pd
import pickle
import quandl
from datetime import datetime
import plotly.offline as py
import plotly.graph_objs as go
import plotly.figure_factory as ff
py.init_notebook_mode(connected=False)
import matplotlib.pyplot as plt

def get_quandl_data(quandl_id):
    '''Download and cache Quandl dataseries'''
    cache_path = '{}.pkl'.format(quandl_id).replace('/', '-')
    try:
        f = open(cache_path, 'rb')
        df = pickle.load(f)
        print('Loaded {} from cache'.format(quandl_id))
    except (OSError, IOError) as e:
        print('Downloading {} from Quandl'.format(quandl_id))
        df = quandl.get(quandl_id, returns="pandas")
        df.to_pickle(cache_path)
        print('Cached {} at {}'.format(quandl_id, cache_path))
    return df


# In[5]: # Pull Kraken BTC price exchange data
btc_usd_price_kraken = get_quandl_data('BCHARTS/KRAKENUSD')
`#THIS IS WORKING OK AND PLOTING CHART`
    btc_trace = go.Scatter(x=btc_usd_price_kraken.index, y=btc_usd_price_kraken['Weighted Price'])
    py.plot([btc_trace])

# Pull pricing data for 3 more BTC exchanges
exchanges = ['COINBASE', 'BITSTAMP', 'ITBIT']
exchange_data = {}
exchange_data['KRAKEN'] = btc_usd_price_kraken

for exchange in exchanges:
    exchange_code = 'BCHARTS/{}USD'.format(exchange)
    btc_exchange_df = get_quandl_data(exchange_code)
    exchange_data[exchange] = btc_exchange_df


def merge_dfs_on_column(dataframes, labels, col):
    '''Merge a single column of each dataframe into a new combined dataframe'''
    series_dict = {}
    for index in range(len(dataframes)):
        series_dict[labels[index]] = dataframes[index][col]

    return pd.DataFrame(series_dict)
btc_usd_datasets = merge_dfs_on_column(list(exchange_data.values()), list(exchange_data.keys()), 'Weighted Price')

print(btc_usd_datasets.tail(10))


def df_scatter(df, title, seperate_y_axis=False, y_axis_label='', scale='linear', initial_hide=False):
    '''Generate a scatter plot of the entire dataframe'''
    label_arr = list(df)
    series_arr = list(map(lambda col: df[col], label_arr))

    layout = go.Layout(
        title=title,
        legend=dict(orientation="h"),
        xaxis=dict(type='date'),
        yaxis=dict(
            title=y_axis_label,
            showticklabels=not seperate_y_axis,
            type=scale
        )
    )

    y_axis_config = dict(
        overlaying='y',
        showticklabels=False,
        type=scale)

    visibility = 'visible'
    if initial_hide:
        visibility = 'legendonly'

    # Form Trace For Each Series
    trace_arr = []
    for index, series in enumerate(series_arr):
        trace = go.Scatter(
            x=series.index,
            y=series,
            name=label_arr[index],
            visible=visibility
        )

        # Add seperate axis for the series
        if seperate_y_axis:
            trace['yaxis'] = 'y{}'.format(index + 1)
            layout['yaxis{}'.format(index + 1)] = y_axis_config
        trace_arr.append(trace)

    fig = go.Figure(data=trace_arr, layout=layout)
#THIS IS NOT PLOTTING PLS. ADVICE
`        py.plot(fig)`