passed in for na_values (GH12224) • Bug in pd.read_csv() which caused BOM files to be incorrectly parsed by not ignoring the BOM (GH4793) • Bug in pd.read_csv() with engine='python' which raised errors notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of the copyright holder nor the names of any das/tests/data/tips. ˓→csv' In [4]: tips = pd.read_csv(url) In [5]: tips.head() Out[5]: total_bill tip sex smoker day time size 0 16.99 1.01 Female No Sun Dinner 2 1 10.34 1.66 Male No Sun Dinner

passed in for na_values (GH12224) • Bug in pd.read_csv() which caused BOM files to be incorrectly parsed by not ignoring the BOM (GH4793) • Bug in pd.read_csv() with engine='python' which raised errors notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of the copyright holder nor the names of any das/tests/data/tips. ˓→csv' In [4]: tips = pd.read_csv(url) In [5]: tips.head() Out[5]: total_bill tip sex smoker day time size 0 16.99 1.01 Female No Sun Dinner 2 1 10.34 1.66 Male No Sun Dinner

passed in for na_values (GH12224) • Bug in pd.read_csv() which caused BOM files to be incorrectly parsed by not ignoring the BOM (GH4793) • Bug in pd.read_csv() with engine='python' which raised errors notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of the copyright holder nor the names of any /pandas/tests/data/tips.csv' In [4]: tips = pd.read_csv(url) In [5]: tips.head() Out[5]: total_bill tip sex smoker day time size 0 16.99 1.01 Female No Sun Dinner 2 1 10.34 1.66 Male No Sun Dinner

passed in for na_values (GH12224) • Bug in pd.read_csv() which caused BOM files to be incorrectly parsed by not ignoring the BOM (GH4793) • Bug in pd.read_csv() with engine='python' which raised errors notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of the copyright holder nor the names of any das/tests/data/tips. ˓→csv' In [4]: tips = pd.read_csv(url) In [5]: tips.head() Out[5]: total_bill tip sex smoker day time size 0 16.99 1.01 Female No Sun Dinner 2 1 10.34 1.66 Male No Sun Dinner

notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of the copyright holder nor the names of any plt.figure() In [3]: plot = rplot.RPlot(tips_data, x=’total_bill’, y=’tip’) In [4]: plot.add(rplot.TrellisGrid([’sex’, ’smoker’])) In [5]: plot.add(rplot.GeomHistogram()) plt.figure() In [8]: plot = rplot.RPlot(tips_data, x=’total_bill’, y=’tip’) In [9]: plot.add(rplot.TrellisGrid([’sex’, ’smoker’])) In [10]: plot.add(rplot.GeomDensity())

passed in for na_values (GH12224) • Bug in pd.read_csv() which caused BOM files to be incorrectly parsed by not ignoring the BOM (GH4793) • Bug in pd.read_csv() with engine='python' which raised errors notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of the copyright holder nor the names of its das/tests/data/tips. ˓→csv' In [4]: tips = pd.read_csv(url) In [5]: tips.head() Out[5]: total_bill tip sex smoker day time size 0 16.99 1.01 Female No Sun Dinner 2 1 10.34 1.66 Male No Sun Dinner

notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of the copyright holder nor the names of its /io/data/csv/tips.csv" ...: ) ...: In [4]: tips = pd.read_csv(url) In [5]: tips Out[5]: total_bill tip sex smoker day time size 0 16.99 1.01 Female No Sun Dinner 2 1 10.34 1.66 Male No Sun Dinner columns): SELECT total_bill, tip, smoker, time FROM tips; With pandas, column selection is done by passing a list of column names to your DataFrame: In [6]: tips[["total_bill", "tip", "smoker", "time"]]

notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of the copyright holder nor the names of its /io/data/csv/tips.csv" ...: ) ...: In [4]: tips = pd.read_csv(url) In [5]: tips Out[5]: total_bill tip sex smoker day time size 0 16.99 1.01 Female No Sun Dinner 2 1 10.34 1.66 Male No Sun Dinner columns): SELECT total_bill, tip, smoker, time FROM tips; With pandas, column selection is done by passing a list of column names to your DataFrame: In [6]: tips[["total_bill", "tip", "smoker", "time"]]

notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of the copyright holder nor the names of its /io/data/csv/tips.csv" ...: ) ...: In [4]: tips = pd.read_csv(url) In [5]: tips Out[5]: total_bill tip sex smoker day time size 0 16.99 1.01 Female No Sun Dinner 2 1 10.34 1.66 Male No Sun Dinner columns): SELECT total_bill, tip, smoker, time FROM tips; With pandas, column selection is done by passing a list of column names to your DataFrame: In [6]: tips[["total_bill", "tip", "smoker", "time"]]

notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of the copyright holder nor the names of its /io/data/csv/tips.csv" ...: ) ...: In [4]: tips = pd.read_csv(url) In [5]: tips Out[5]: total_bill tip sex smoker day time size 0 16.99 1.01 Female No Sun Dinner 2 1 10.34 1.66 Male No Sun Dinner columns): SELECT total_bill, tip, smoker, time FROM tips; With pandas, column selection is done by passing a list of column names to your DataFrame: In [6]: tips[["total_bill", "tip", "smoker", "time"]]