# install required packages !pip install jupyter_dash==0.4.0 !pip install pandas !pip install openpyxl

# code chunk to import necessary libraries from jupyter_dash import JupyterDash from dash import dcc, html from dash.dependencies import Input, Output from plotly import data import plotly.express as px import pandas as pd

# read in most popular streaming service data pop_data = pd.read_excel( "statistic_id1035628_most-in-demand-video-streaming-services-worldwide-2020-by-share-of-demand.xlsx", sheet_name=1, skiprows=5, usecols="B:D", header = None, ) print(pop_data)

# create horizontal bar plot for pop_data dataset pop_plot = px.bar(pop_data, x=2, y=1, orientation='h', hover_data=[1, 2], height=400, title='Most popular video streaming service based on share of audience demand for digital originals worldwide in 2020', labels={ "2": "Audience demand share (%)", "1": "" }) print(pop_data) pop_plot.show()

# read in most popular US streaming service data us_pop_data = pd.read_excel( "statistic_id910875_leading-us-video-streaming-services-2019-by-monthly-average-users.xlsx", sheet_name=1, skiprows=5, usecols="B:C", header = None, ) print(us_pop_data)

# create horizontal bar plot for us_pop_data dataset us_pop_plot = px.bar(us_pop_data, x=2, y=1, orientation='h', hover_data=[1, 2], height=400, title='Most popular video streaming services in the United States as of September 2019, by monthly average users (in millions)', labels={ "2": "Number of users (millions)", "1": "" }) print(us_pop_data) us_pop_plot.show()

# read in most viewed tv show per year in UK uk_show_data = pd.read_excel( "statistic_id1169502_most-viewed-television-program-every-year-in-the-united-kingdom--uk--2000-2019.xlsx", sheet_name=1, skiprows=5, usecols="B:C", header = None, ) print(uk_show_data)

# create horizontal bar plot for us_pop_data dataset uk_show_plot = px.bar( uk_show_data, x=2, y=1, orientation="h", hover_data=[1, 2], title="Viewing figures for the most watched television program of each year in the United Kingdom (UK) from 2000 to 2019 (in millions)", labels={"2": "Audience (millions)", "1": ""}, ) print(uk_show_data) uk_show_plot.show()

# read in digital video viewers in UK uk_digital_data = pd.read_excel( "statistic_id193959_digital-video-viewers-in-the-united-kingdom--uk--2012-2019.xlsx", sheet_name=1, skiprows=5, usecols="B:C", header = None, ) print(uk_digital_data)

# create horizontal bar plot for uk_digital_plot dataset uk_digital_plot = px.bar( uk_digital_data, x=2, y=1, orientation="h", hover_data=[1, 2], title="Digital video viewers in the United Kingdom from 2012 to 2019 (in millions)", labels={"2": "Viewers (millions)", "1": ""}, ) print(uk_digital_data) uk_digital_plot.show()

# read in IMDB TV audience US data us_imdb_data = pd.read_excel( "statistic_id1128393_imdb-tv-audience-us-2020-by-generation.xlsx", sheet_name=1, skiprows=5, usecols="B:D", header = None, ) print(us_imdb_data)

# create horizontal bar plot for us_imdb_data dataset us_imdb_plot = px.bar( us_imdb_data, x=2, y=1, orientation="h", hover_data=[1, 2], title="Share of adults who used IMDB TV in the last year in the United States as of February 2020, by generation", labels={"2": "Share of respondents (%)", "1": ""}, ) print(us_imdb_data) us_imdb_plot.show()

# read in video watching by device in GB data gb_device_data = pd.read_excel( "statistic_id289079_online-video-watching-penetration-in-great-britain-2020-by-device.xlsx", sheet_name=1, skiprows=4, usecols="B:H", header = 0, ) print(gb_device_data)

# going to need to restructure the data from wide to long gb_device_data = gb_device_data.drop("Unnamed: 7", 1) gb_device_data = pd.melt( gb_device_data, id_vars=["Unnamed: 1"], var_name="device", value_name="value" ) # now create a grouped plot gb_device_plot = px.bar( gb_device_data, y="value", x="Unnamed: 1", color="device", barmode="group", title="Penetration of online video watching in Great Britain in 2020, by device", labels={"value": "Share of respondents (%)", "Unnamed: 1": ""}, ) gb_device_plot.show()

# read in subscriber market share data subscribers_data = pd.read_excel( "statistic_id1052803_svod-platforms-subscriber-market-share-worldwide-in-2024.xlsx", sheet_name=1, skiprows=5, usecols="B:D", header = None, ) print(subscribers_data)

# create horizontal bar plot for subscribers_data plot subscribers_plot = px.bar( subscribers_data, x=2, y=1, orientation="h", hover_data=[1, 2], title="Estimated subscriber market share of selected SVOD services worldwide in 2024", labels={"2": "Subscriber market share (%)", "1": ""}, ) print(subscribers_data) subscribers_plot.show()

app = JupyterDash(__name__) app.layout = html.Div( [ html.P("Select plot:"), dcc.Dropdown( id="plot", value="pop_plot", options=[ { "value": "pop_plot", "label": "Most popular video streaming service based on share of audience demand for digital originals worldwide in 2020", }, { "value": "us_pop_plot", "label": "Most popular video streaming services in the United States as of September 2019, by monthly average users (in millions)", }, { "value": "uk_show_plot", "label": "Viewing figures for the most watched television program of each year in the United Kingdom (UK) from 2000 to 2019 (in millions)", }, { "value": "uk_digital_plot", "label": "Digital video viewers in the United Kingdom from 2012 to 2019 (in millions)", }, { "value": "us_imdb_plot", "label": "Share of adults who used IMDB TV in the last year in the United States as of February 2020, by generation", }, { "value": "gb_device_plot", "label": "Penetration of online video watching in Great Britain in 2020, by device", }, { "value": "subscribers_plot", "label": "Estimated subscriber market share of selected SVOD services worldwide in 2024", }, ], clearable=False, ), dcc.Graph(id="charts"), ] ) @app.callback(Output("charts", "figure"), Input("plot", "value")) def generate_chart(plot): if plot == "pop_plot": fig = pop_plot if plot == "us_pop_plot": fig = us_pop_plot if plot == "uk_show_plot": fig = uk_show_plot if plot == "uk_digital_plot": fig = uk_digital_plot if plot == "us_imdb_plot": fig = us_imdb_plot if plot == "gb_device_plot": fig = gb_device_plot if plot == "subscribers_plot": fig = subscribers_plot return fig app.run_server( mode="external", port=8080, host="0.0.0.0", dev_tools_ui=True, dev_tools_hot_reload=True, threaded=True, )