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simplified code - removed .loc and aggregate() #79

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Oct 24, 2024
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simplified code - removed .loc and aggregate() #79

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10 changes: 5 additions & 5 deletions ...apter 4 - Find out on which weekday people bike the most with groupby and aggregate.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -348,7 +348,7 @@
}
],
"source": [
"berri_bikes.loc[:,'weekday'] = berri_bikes.index.weekday\n",
"berri_bikes['weekday'] = berri_bikes.index.weekday\n",
"berri_bikes[:5]"
]
},
Expand All @@ -367,7 +367,7 @@
"\n",
"Dataframes have a `.groupby()` method that is similar to SQL groupby, if you're familiar with that. I'm not going to explain more about it right now -- if you want to to know more, [the documentation](http://pandas.pydata.org/pandas-docs/stable/groupby.html) is really good.\n",
"\n",
"In this case, `berri_bikes.groupby('weekday').aggregate(sum)` means \"Group the rows by weekday and then add up all the values with the same weekday\"."
"In this case, `berri_bikes.groupby('weekday').sum()` means \"Group the rows by weekday and then add up all the values with the same weekday\"."
]
},
{
Expand Down Expand Up @@ -454,7 +454,7 @@
}
],
"source": [
"weekday_counts = berri_bikes.groupby('weekday').aggregate(sum)\n",
"weekday_counts = berri_bikes.groupby('weekday').sum()\n",
"weekday_counts"
]
},
Expand Down Expand Up @@ -634,10 +634,10 @@
" index_col='Date')\n",
"# Add the weekday column\n",
"berri_bikes = bikes[['Berri 1']].copy()\n",
"berri_bikes.loc[:,'weekday'] = berri_bikes.index.weekday\n",
"berri_bikes['weekday'] = berri_bikes.index.weekday\n",
"\n",
"# Add up the number of cyclists by weekday, and plot!\n",
"weekday_counts = berri_bikes.groupby('weekday').aggregate(sum)\n",
"weekday_counts = berri_bikes.groupby('weekday').sum()\n",
"weekday_counts.index = ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday']\n",
"weekday_counts.plot(kind='bar')"
]
Expand Down