@@ -2599,14 +2599,14 @@ <h3 id="format-2">Format</h3><div><h4 id="forstandardtypesizesandmanualalignment
25992599<Sr> = <Sr>.fillna(<el>) < span class ="hljs-comment "> # Or: <Sr>.agg/transform/map(lambda <el>: <el>)</ span >
26002600</ code > </ pre > </ div >
26012601
2602- < pre > < code class ="python language-python hljs "> < span class ="hljs-meta "> >>> </ span > sr = pd.Series([< span class ="hljs-number "> 1 </ span > , < span class ="hljs-number "> 2 </ span > ], index=[< span class ="hljs-string "> 'x'</ span > , < span class ="hljs-string "> 'y'</ span > ])
2603- x < span class ="hljs-number "> 1 </ span >
2604- y < span class ="hljs-number "> 2 </ span >
2602+ < pre > < code class ="python language-python hljs "> < span class ="hljs-meta "> >>> </ span > sr = pd.Series([< span class ="hljs-number "> 2 </ span > , < span class ="hljs-number "> 3 </ span > ], index=[< span class ="hljs-string "> 'x'</ span > , < span class ="hljs-string "> 'y'</ span > ])
2603+ x < span class ="hljs-number "> 2 </ span >
2604+ y < span class ="hljs-number "> 3 </ span >
26052605</ code > </ pre >
26062606< pre > < code class ="python hljs "> ┏━━━━━━━━━━━━━━━┯━━━━━━━━━━━━━┯━━━━━━━━━━━━━┯━━━━━━━━━━━━━━━┓
26072607┃ │ < span class ="hljs-string "> 'sum'</ span > │ [< span class ="hljs-string "> 'sum'</ span > ] │ {< span class ="hljs-string "> 's'</ span > : < span class ="hljs-string "> 'sum'</ span > } ┃
26082608┠───────────────┼─────────────┼─────────────┼───────────────┨
2609- ┃ sr.apply(…) │ < span class ="hljs-number "> 3 </ span > │ sum < span class ="hljs-number "> 3 </ span > │ s < span class ="hljs-number "> 3 </ span > ┃
2609+ ┃ sr.apply(…) │ < span class ="hljs-number "> 5 </ span > │ sum < span class ="hljs-number "> 5 </ span > │ s < span class ="hljs-number "> 5 </ span > ┃
26102610┃ sr.agg(…) │ │ │ ┃
26112611┗━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━┷━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━┛
26122612
@@ -2756,12 +2756,12 @@ <h3 id="format-2">Format</h3><div><h4 id="forstandardtypesizesandmanualalignment
27562756<DF> = <GB>.fillna(<el>) < span class ="hljs-comment "> # Or: <GB>.transform(lambda <Sr>: <Sr>)</ span >
27572757</ code > </ pre > </ div >
27582758
2759- < pre > < code class ="python language-python hljs "> < span class ="hljs-meta "> >>> </ span > gb = df.groupby(< span class ="hljs-string "> 'z'</ span > )
2760- x y z
2761- < span class =" hljs-number " > 3 </ span > : a < span class ="hljs-number "> 1</ span > < span class ="hljs-number "> 2</ span > < span class ="hljs-number "> 3</ span >
2762- < span class =" hljs-number " > 6 </ span > : b < span class =" hljs-number " > 4 </ span > < span class =" hljs-number " > 5 </ span > < span class =" hljs-number " > 6 </ span >
2763- c < span class ="hljs-number "> 7 </ span > < span class ="hljs-number "> 8 </ span > < span class ="hljs-number "> 6</ span >
2764- </ code > </ pre >
2759+ < pre > < code class ="python language-python hljs "> < span class ="hljs-meta "> >>> </ span > gb = df.groupby(< span class ="hljs-string "> 'z'</ span > ); gb.apply(print)
2760+ x y z
2761+ a < span class ="hljs-number "> 1</ span > < span class ="hljs-number "> 2</ span > < span class ="hljs-number "> 3</ span >
2762+ x y z
2763+ b < span class ="hljs-number "> 4 </ span > < span class ="hljs-number "> 5 </ span > < span class ="hljs-number "> 6</ span >
2764+ c < span class =" hljs-number " > 7 </ span > < span class =" hljs-number " > 8 </ span > < span class =" hljs-number " > 6 </ span > </ code > </ pre >
27652765< pre > < code class ="python hljs "> ┏━━━━━━━━━━━━━━━━━┯━━━━━━━━━━━━━┯━━━━━━━━━━━━━┯━━━━━━━━━━━━━┯━━━━━━━━━━━━━━━┓
27662766┃ │ < span class ="hljs-string "> 'sum'</ span > │ < span class ="hljs-string "> 'rank'</ span > │ [< span class ="hljs-string "> 'rank'</ span > ] │ {< span class ="hljs-string "> 'x'</ span > : < span class ="hljs-string "> 'rank'</ span > } ┃
27672767┠─────────────────┼─────────────┼─────────────┼─────────────┼───────────────┨
@@ -2783,14 +2783,14 @@ <h3 id="format-2">Format</h3><div><h4 id="forstandardtypesizesandmanualalignment
27832783</ code > </ pre > </ div >
27842784
27852785
2786- < 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 >
2787- < span class ="hljs-keyword "> from </ span > plotly.express < span class ="hljs-keyword "> import </ span > line
2788- <Figure> = line(<DF>, x=<col_name>, y=<col_name>) < span class ="hljs-comment "> # Or: line(x=<list>, y=<list>)</ span >
2786+ < 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 pandas plotly kaleido</ span >
2787+ < span class ="hljs-keyword "> import </ span > pandas < span class =" hljs-keyword " > as </ span > pd, plotly.express < span class ="hljs-keyword "> as </ span > ex
2788+ <Figure> = ex. line(<DF>, x=<col_name>, y=<col_name>) < span class ="hljs-comment "> # Or: ex. line(x=<list>, y=<list>)</ span >
27892789<Figure>.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 "> # `paper_bgcolor='rgb(0, 0, 0)'`.</ span >
27902790<Figure>.write_html/json/image(< span class ="hljs-string "> '<path>'</ span > ) < span class ="hljs-comment "> # Also <Figure>.show().</ span >
27912791</ code > </ pre > </ div >
27922792
2793- < div > < h4 id ="displaysalinechartoftotalcoronavirusdeathspermilliongroupedbycontinent "> Displays a line chart of total coronavirus deaths per million grouped 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 > ,
2793+ < div > < h4 id ="displaysalinechartoftotalcoronavirusdeathspermilliongroupedbycontinent "> Displays a line chart of total coronavirus deaths per million grouped by continent:</ h4 > < p > </ p > < div id ="2a950764-39fc-416d-97fe-0a6226a3095f " class ="plotly-graph-div " style ="height:321px ; 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 > ,
27942794 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 > ])
27952795continents = pd.read_csv(< span class ="hljs-string "> 'https://gist.githubusercontent.com/stevewithington/20a69c0b6d2ff'</ span >
27962796 < span class ="hljs-string "> '846ea5d35e5fc47f26c/raw/country-and-continent-codes-list-csv.csv'</ span > ,
@@ -2800,7 +2800,7 @@ <h3 id="format-2">Format</h3><div><h4 id="forstandardtypesizesandmanualalignment
28002800df[< span class ="hljs-string "> 'Total Deaths per Million'</ span > ] = df.total_deaths * < span class ="hljs-number "> 1e6</ span > / df.population
28012801df = df[df.date > < span class ="hljs-string "> '2020-03-14'</ span > ]
28022802df = df.rename({< span class ="hljs-string "> 'date'</ span > : < span class ="hljs-string "> 'Date'</ span > , < span class ="hljs-string "> 'Continent_Name'</ span > : < span class ="hljs-string "> 'Continent'</ span > }, axis=< span class ="hljs-string "> 'columns'</ span > )
2803- line(df, x=< span class ="hljs-string "> 'Date'</ span > , y=< span class ="hljs-string "> 'Total Deaths per Million'</ span > , color=< span class ="hljs-string "> 'Continent'</ span > ).show()
2803+ ex. line(df, x=< span class ="hljs-string "> 'Date'</ span > , y=< span class ="hljs-string "> 'Total Deaths per Million'</ span > , color=< span class ="hljs-string "> 'Continent'</ span > ).show()
28042804</ code > </ pre > </ div >
28052805
28062806
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