First commit

README.org

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+* Test
+
+test12

interactive-plot.py

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+import pandas as pd
+import plotly.graph_objects as go
+from plotly.subplots import make_subplots
+import dash
+import dash_core_components as dcc
+import dash_html_components as html
+from dash.dependencies import Input, Output
+
+
+# The code below fetches the data from the "Our World in Data" Github page. 
+# This is the data behind this graph/table: https://ourworldindata.org/grapher/cumulative-co-emissions
+# If the url does not work you can also use the data provided, by uncommenting the line below.
+df = pd.read_csv('/home/misha/Nextcloud/scripts_misha/klad/data/owid-co2-data.csv', header =0)
+# df = pd.read_csv('https://nyc3.digitaloceanspaces.com/owid-public/data/co2/owid-co2-data.csv', header=0)
+
+# Select only data for World
+df = df[df['country'] == 'World']
+
+# Select year and Cumulative CO2
+df = df[['year','cumulative_co2']]
+
+# Turn year to integer
+df['year'] = df['year'].astype(int)
+
+# Subtract from every cumulative value what has been emitted until 1750
+df['cumulative_co2']=df['cumulative_co2']-df['cumulative_co2'].iloc[0]
+
+# For every row:
+# 1. Calculate difference between "cumulative CO2 in year i" and "cumulative CO2 in last year" 
+# 2. Divide this difference with "cumulative CO2 in last year" 
+
+sums = []
+
+for i in range(len(df)):
+    share_gen = (df['cumulative_co2'].iloc[-1]-df['cumulative_co2'].iloc[i])/df['cumulative_co2'].iloc[-1]*100
+    sums.append(share_gen)
+
+# Add the new column of sums to the original DataFrame
+df['share_gen'] = sums
+
+# Select every fifth row
+df = df.iloc[::5]
+
+# Select data for people who were born in the last 100 years
+scope = int(100/5)
+df = df.tail(scope).reset_index(drop=True)
+
+min_year = df['year'].iloc[0].item()
+max_year = df['year'].iloc[-1].item()
+
+# Create a Dash application
+app = dash.Dash(__name__)
+
+
+app.layout = html.Div([
+    html.P('1. Works best on Desktop 2. Use the slider to adjust the graph 3. Hoover mouse over graph to see (i.a.) the download button', style={'textAlign': 'left'}),
+    dcc.Slider(
+        id='year-slider',
+        min=min_year,
+        max=max_year,
+        value=1985,
+        marks={str(year): str(year) for year in range(min_year,max_year+1, 5)},
+        step=None
+    ),
+
+    dcc.Graph(
+        id="sine-graph",
+        style={'height': '90vh', 'width': '100vw'}
+    ),
+])
+
+@app.callback(
+    Output("sine-graph", "figure"),
+    [Input("year-slider", "value")]
+)
+
+
+
+def update_graph(year_born):
+
+
+
+    # Round the year born to intervals of 5
+    year_born_round = int(5 * round(float(year_born)/5))
+
+    # Find index in df of year born
+    year_born_index = df[df['year'] == year_born_round].index.tolist()[0]
+
+    # data frame to plotly graph
+    fig = go.Figure(data=[
+    go.Bar(y=df['year'], x=df['share_gen'], orientation='h',
+        showlegend=False,
+        marker_color=['silver' if i != year_born_index else 'lightcoral' for i in range(df.shape[0])],
+        name = '')
+    ])
+
+    subtitle= "See:  <a href=\"https://git.pub.solar/misha/share_CO2_generation\">https://git.pub.solar/misha/share_CO2_generation</a> (original from <a href=\"https://x.com/neilrkaye/status/1365247133507604486\">https://x.com/neilrkaye/status/1365247133507604486</a>)"
+    explainer = "If you were born in %s, %s%% of<br>the total amount of CO2 that has <br>been emitted since 1750, has been<br>emitted in your lifetime." % (int(df['year'].iloc[year_born_index].item()), int(df['share_gen'].iloc[year_born_index].item()))
+
+    (int(df['year'].iloc[year_born_index].item()), int(df['share_gen'].iloc[year_born_index].item()))
+
+
+    # Create subplot for vertical line
+    fig_vline = go.Figure(data=[go.Scatter(x = [df['share_gen'].iloc[year_born_index]]*2, 
+                                            y=[df['year'].min()-2.5, df['year'].iloc[year_born_index]], mode='lines',
+                                            showlegend=False,
+                                            line=dict(color='lightcoral'))])
+
+    # Merge figures
+    fig.add_trace(fig_vline.data[0])
+
+
+    fig.update_layout(title_text='Percentage of global CO2 emissions since 1750\n occurring in your lifetime (last updated: %s)<br><sub>%s</sub>' % (df['year'].iloc[-1],subtitle),
+                    xaxis_title="percentage", yaxis_title="year of birth")
+
+
+    fig.update_yaxes(range=[df['year'].min()-2.5, df['year'].max()+2.5],
+                    tickmode = 'array',
+                    tickvals = list(range(df['year'].min(), df['year'].max(), 5)))
+
+    fig.add_annotation(
+        text=explainer,
+        xref="paper", yref="paper",
+        x=0.95, y=0.95, showarrow=False,
+        align="left",
+        font=dict(size=16),
+        bgcolor="lightcoral",
+        borderwidth=2
+    )
+
+    return fig
+
+
+if __name__ == '__main__':
+    app.run_server(debug=True,host='0.0.0.0')