Pandas

gto76 · gto76 · commit c074e81e63d6 · 2020-09-24T00:18:42.000+02:00
diff --git a/README.md b/README.md
@@ -3382,7 +3382,9 @@ import plotly.graph_objects as go
 import datetime
 
 def main():
-    display_data(wrangle_data(*scrape_data()))
+    data = scrape_data()
+    df = wrangle_data(*data)
+    display_data(df)
 
 def scrape_data():
     def scrape_yahoo(id_):
@@ -3400,8 +3402,8 @@ def scrape_data():
 def wrangle_data(covid, dow, gold, bitcoin):
     df = pd.concat([dow, gold, bitcoin], axis=1)
     df = df.sort_index().interpolate()
-    df = df.loc['2020-02-23':].iloc[:-2]
     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')
 
diff --git a/index.html b/index.html
@@ -2866,7 +2866,9 @@
 <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>
-    display_data(wrangle_data(*scrape_data()))
+    data = scrape_data()
+    df = wrangle_data(*data)
+    display_data(df)
 
 <span class="hljs-function"><span class="hljs-keyword">def</span> <span class="hljs-title">scrape_data</span><span class="hljs-params">()</span>:</span>
     <span class="hljs-function"><span class="hljs-keyword">def</span> <span class="hljs-title">scrape_yahoo</span><span class="hljs-params">(id_)</span>:</span>
@@ -2884,8 +2886,8 @@
 <span class="hljs-function"><span class="hljs-keyword">def</span> <span class="hljs-title">wrangle_data</span><span class="hljs-params">(covid, dow, gold, bitcoin)</span>:</span>
     df = pd.concat([dow, gold, bitcoin], axis=<span class="hljs-number">1</span>)
     df = df.sort_index().interpolate()
-    df = df.loc[<span class="hljs-string">'2020-02-23'</span>:].iloc[:<span class="hljs-number">-2</span>]
     df = df.rolling(<span class="hljs-number">10</span>, min_periods=<span class="hljs-number">1</span>, center=<span class="hljs-keyword">True</span>).mean()
+    df = df.loc[<span class="hljs-string">'2020-02-23'</span>:].iloc[:<span class="hljs-number">-2</span>]
     df = df / df.iloc[<span class="hljs-number">0</span>] * <span class="hljs-number">100</span>
     <span class="hljs-keyword">return</span> pd.concat([covid, df], axis=<span class="hljs-number">1</span>, join=<span class="hljs-string">'inner'</span>)
 
