diff --git a/README.md b/README.md
index 3ce9a11..07feb9e 100644
--- a/README.md
+++ b/README.md
@@ -3348,14 +3348,15 @@ Plotly
 ```python
 # $ pip3 install plotly kaleido
 from plotly.express import line
-<Figure> = line(<DF>, x=<col_name>, y=<col_name>)   # Or: line(x=<list>, y=<list>)
-<Figure>.write_html/json/image('<path>')            # Also: <Figure>.show()
+<Figure> = line(<DF>, x=<col_name>, y=<col_name>)        # Or: line(x=<list>, y=<list>)
+<Figure>.update_layout(margin=dict(t=0, r=0, b=0, l=0))  # Or: paper_bgcolor='rgba(0, 0, 0, 0)'
+<Figure>.write_html/json/image('<path>')                 # Also: <Figure>.show()
 ```
 
 #### Covid deaths by continent:
 
 ![Covid Deaths](web/covid_deaths.png)
-<div id="2a950764-39fc-416d-97fe-0a6226a3095f" class="plotly-graph-div" style="height:360px; width:100%;"></div>
+<div id="2a950764-39fc-416d-97fe-0a6226a3095f" class="plotly-graph-div" style="height:340px; width:100%;"></div>
 
 ```python
 covid = pd.read_csv('https://covid.ourworldindata.org/data/owid-covid-data.csv', 
@@ -3374,9 +3375,10 @@ line(df, x='Date', y='Total Deaths per Million', color='Continent').show()
 #### Confirmed covid cases, Dow Jones, gold, and Bitcoin price:
 
 ![Covid Cases](web/covid_cases.png)
-<div id="e23ccacc-a456-478b-b467-7282a2165921" class="plotly-graph-div" style="height:333px; width:100%;"></div>
+<div id="e23ccacc-a456-478b-b467-7282a2165921" class="plotly-graph-div" style="height:315px; width:100%;"></div>
 
 ```python
+import pandas as pd
 import plotly.graph_objects as go
 import datetime
 
diff --git a/index.html b/index.html
index 431a371..42be520 100644
--- a/index.html
+++ b/index.html
@@ -2845,11 +2845,12 @@ c  <span class="hljs-number">7</span>  <span class="hljs-number">8</span>
 
 <div><h2 id="plotly"><a href="#plotly" name="plotly">#</a>Plotly</h2><pre><code class="python language-python hljs"><span class="hljs-comment"># $ pip3 install plotly kaleido</span>
 <span class="hljs-keyword">from</span> plotly.express <span class="hljs-keyword">import</span> line
-&lt;Figure&gt; = line(&lt;DF&gt;, x=&lt;col_name&gt;, y=&lt;col_name&gt;)   <span class="hljs-comment"># Or: line(x=&lt;list&gt;, y=&lt;list&gt;)</span>
-&lt;Figure&gt;.write_html/json/image(<span class="hljs-string">'&lt;path&gt;'</span>)            <span class="hljs-comment"># Also: &lt;Figure&gt;.show()</span>
+&lt;Figure&gt; = line(&lt;DF&gt;, x=&lt;col_name&gt;, y=&lt;col_name&gt;)        <span class="hljs-comment"># Or: line(x=&lt;list&gt;, y=&lt;list&gt;)</span>
+&lt;Figure&gt;.update_layout(margin=dict(t=<span class="hljs-number">0</span>, r=<span class="hljs-number">0</span>, b=<span class="hljs-number">0</span>, l=<span class="hljs-number">0</span>))  <span class="hljs-comment"># Or: paper_bgcolor='rgba(0, 0, 0, 0)'</span>
+&lt;Figure&gt;.write_html/json/image(<span class="hljs-string">'&lt;path&gt;'</span>)                 <span class="hljs-comment"># Also: &lt;Figure&gt;.show()</span>
 </code></pre></div>
 
-<div><h4 id="coviddeathsbycontinent">Covid deaths by continent:</h4><p></p><div id="2a950764-39fc-416d-97fe-0a6226a3095f" class="plotly-graph-div" style="height:360px; width:100%;"></div><pre><code class="python language-python hljs">covid = pd.read_csv(<span class="hljs-string">'https://covid.ourworldindata.org/data/owid-covid-data.csv'</span>, 
+<div><h4 id="coviddeathsbycontinent">Covid deaths by continent:</h4><p></p><div id="2a950764-39fc-416d-97fe-0a6226a3095f" class="plotly-graph-div" style="height:340px; width:100%;"></div><pre><code class="python language-python hljs">covid = pd.read_csv(<span class="hljs-string">'https://covid.ourworldindata.org/data/owid-covid-data.csv'</span>, 
                     usecols=[<span class="hljs-string">'iso_code'</span>, <span class="hljs-string">'date'</span>, <span class="hljs-string">'total_deaths'</span>, <span class="hljs-string">'population'</span>])
 continents = pd.read_csv(<span class="hljs-string">'https://datahub.io/JohnSnowLabs/country-and-continent-codes-'</span> + \
                          <span class="hljs-string">'list/r/country-and-continent-codes-list-csv.csv'</span>,
@@ -2864,7 +2865,8 @@ line(df, x=<span class="hljs-string">'Date'</span>, y=<span class="hljs-string">
 
 
 
-<div><h4 id="confirmedcovidcasesdowjonesgoldandbitcoinprice">Confirmed covid cases, Dow Jones, gold, and Bitcoin price:</h4><p></p><div id="e23ccacc-a456-478b-b467-7282a2165921" class="plotly-graph-div" style="height:333px; width:100%;"></div><pre><code class="python language-python hljs"><span class="hljs-keyword">import</span> plotly.graph_objects <span class="hljs-keyword">as</span> go
+<div><h4 id="confirmedcovidcasesdowjonesgoldandbitcoinprice">Confirmed covid cases, Dow Jones, gold, and Bitcoin price:</h4><p></p><div id="e23ccacc-a456-478b-b467-7282a2165921" class="plotly-graph-div" style="height:315px; width:100%;"></div><pre><code class="python language-python hljs"><span class="hljs-keyword">import</span> pandas <span class="hljs-keyword">as</span> pd
+<span class="hljs-keyword">import</span> plotly.graph_objects <span class="hljs-keyword">as</span> go
 <span class="hljs-keyword">import</span> datetime
 
 <span class="hljs-function"><span class="hljs-keyword">def</span> <span class="hljs-title">main</span><span class="hljs-params">()</span>:</span>
diff --git a/web/covid_cases.js b/web/covid_cases.js
index e3b9dcb..3bc9fc4 100644
--- a/web/covid_cases.js
+++ b/web/covid_cases.js
@@ -4,8 +4,6 @@ window.PLOTLYENV=window.PLOTLYENV || {};
 if (document.getElementById("e23ccacc-a456-478b-b467-7282a2165921")) {
     Plotly.newPlot(
         'e23ccacc-a456-478b-b467-7282a2165921',
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96.47253146524923, 96.37428920729418, 96.4574374092648, 96.31694566090496, 96.22665225640687, 96.13070266327892], "yaxis": "y2"}, {"name": "Gold", "type": "scatter", "x": ["2020-02-23", "2020-02-24", "2020-02-25", "2020-02-26", "2020-02-27", "2020-02-28", "2020-02-29", "2020-03-01", "2020-03-02", "2020-03-03", "2020-03-04", "2020-03-05", "2020-03-06", "2020-03-07", "2020-03-08", "2020-03-09", "2020-03-10", "2020-03-11", "2020-03-12", "2020-03-13", "2020-03-14", "2020-03-15", "2020-03-16", "2020-03-17", "2020-03-18", "2020-03-19", "2020-03-20", "2020-03-21", "2020-03-22", "2020-03-23", "2020-03-24", "2020-03-25", "2020-03-26", "2020-03-27", "2020-03-28", "2020-03-29", "2020-03-30", "2020-03-31", "2020-04-01", "2020-04-02", "2020-04-03", "2020-04-04", "2020-04-05", "2020-04-06", "2020-04-07", "2020-04-08", "2020-04-09", "2020-04-10", "2020-04-11", "2020-04-12", "2020-04-13", "2020-04-14", "2020-04-15", "2020-04-16", "2020-04-17", "2020-04-18", "2020-04-19", "2020-04-20", "2020-04-21", 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diff --git a/web/covid_deaths.js b/web/covid_deaths.js
index da67c28..3a99766 100644
--- a/web/covid_deaths.js
+++ b/web/covid_deaths.js
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+};
diff --git a/web/update_plots.py b/web/update_plots.py
new file mode 100755
index 0000000..259e2e7
--- /dev/null
+++ b/web/update_plots.py
@@ -0,0 +1,110 @@
+#!/usr/bin/env python3
+#
+# Usage: ./update_plots.py
+# Updates plots from the Plotly section so they show the latest data.
+
+from pathlib import Path
+from datetime import date, time, datetime, timedelta
+import pandas as pd
+from plotly.express import line
+import plotly.graph_objects as go
+
+
+def main():
+    print('Updating covid deaths...')
+    update_covid_deaths()
+    print('Updating covid cases...')
+    update_confirmed_cases()
+
+
+def update_covid_deaths():
+    def update_readme(date_treshold):
+        lines = read_file('../README.md')
+        out = [re.sub("df.date < '\d{4}-\d{2}-\d{2}'", f"df.date < '{date_treshold}'", line) 
+                   for line in lines]
+        write_to_file('../README.md', out)
+    covid = pd.read_csv('https://covid.ourworldindata.org/data/owid-covid-data.csv', 
+                        usecols=['iso_code', 'date', 'total_deaths', 'population'])
+    continents = pd.read_csv('https://datahub.io/JohnSnowLabs/country-and-continent-codes-' + \
+                             'list/r/country-and-continent-codes-list-csv.csv',
+                             usecols=['Three_Letter_Country_Code', 'Continent_Name'])
+    df = pd.merge(covid, continents, left_on='iso_code', right_on='Three_Letter_Country_Code')
+    df = df.groupby(['Continent_Name', 'date']).sum().reset_index()
+    df['Total Deaths per Million'] = df.total_deaths * 1e6 / df.population
+    date_treshold = str(date.today() - timedelta(days=2))
+    df = df[('2020-03-14' < df.date) & (df.date < date_treshold)]
+    df = df.rename({'date': 'Date', 'Continent_Name': 'Continent'}, axis='columns')
+    f = line(df, x='Date', y='Total Deaths per Million', color='Continent')
+    f.update_layout(margin=dict(t=24, b=0), paper_bgcolor='rgba(0, 0, 0, 0)')
+    update_file('covid_deaths.js', f)
+    update_readme(date_treshold)
+
+
+def update_confirmed_cases():
+    def main():
+        df = wrangle_data(*scrape_data())
+        f = get_figure(df)
+        update_file('covid_cases.js', f)
+
+    def scrape_data():
+        def scrape_yahoo(id_):
+            BASE_URL = 'https://query1.finance.yahoo.com/v7/finance/download/'
+            now = int(datetime.now().timestamp())
+            url = f'{BASE_URL}{id_}?period1=1579651200&period2={now}&interval=1d&events=history'
+            return pd.read_csv(url, usecols=['Date', 'Close']).set_index('Date').Close
+        covid = pd.read_csv('https://covid.ourworldindata.org/data/owid-covid-data.csv',
+                            usecols=['date', 'total_cases'])
+        covid = covid.groupby('date').sum()
+        dow, gold, bitcoin = [scrape_yahoo(id_) for id_ in ('^DJI', 'GC=F', 'BTC-USD')]
+        dow.name, gold.name, bitcoin.name = 'Dow Jones', 'Gold', 'Bitcoin'
+        return covid, dow, gold, bitcoin
+
+    def wrangle_data(covid, dow, gold, bitcoin):
+        df = pd.concat([dow, gold, bitcoin], axis=1)
+        df = df.sort_index().interpolate()
+        df = df.rolling(10, min_periods=1, center=True).mean()
+        df = df.loc['2020-02-23':].iloc[:-2]
+        df = (df / df.iloc[0]) * 100
+        return pd.concat([covid, df], axis=1, join='inner')
+
+    def get_figure(df):
+        def get_trace(col_name):
+            return go.Scatter(x=df.index, y=df[col_name], name=col_name, yaxis='y2')
+        traces = [get_trace(col_name) for col_name in df.columns[1:]]
+        traces.append(go.Scatter(x=df.index, y=df.total_cases, name='Total Cases', yaxis='y1'))
+        figure = go.Figure()
+        figure.add_traces(traces)
+        figure.update_layout(
+            yaxis1=dict(title='Total Cases', rangemode='tozero'),
+            yaxis2=dict(title='%', rangemode='tozero', overlaying='y', side='right'),
+            legend=dict(x=1.1),
+            margin=dict(t=24, b=0),
+            paper_bgcolor='rgba(0, 0, 0, 0)'
+        )
+        return figure
+
+    main()
+
+
+def update_file(filename, figure):
+    lines = read_file(filename)
+    out = lines[:6] + [f'        {figure.to_json()}\n', '    )\n', '};\n']
+    write_to_file(filename, out)
+
+
+###
+##  UTIL
+#
+
+def read_file(filename):
+    with open(filename, encoding='utf-8') as file:
+        return file.readlines()
+
+
+def write_to_file(filename, lines):
+    with open(filename, 'w', encoding='utf-8') as file:
+        file.writelines(lines)
+
+
+if __name__ == '__main__':
+    main()