Pandas Dataframe to Seaborn Grouped Barchart

The trick is to transform the pandas df from wide to long format

Step 1: Prepare data

import seaborn as snsnp.random.seed(123)index = np.random.randint(1,100,10)x1 = pd.date_range('2000-01-01','2015-01-01').map(lambda t: t.strftime('%Y-%m-%d'))dts = np.random.choice(x1,10)benchmark = np.random.randn(10)portfolio = np.random.randn(10)df = pd.DataFrame({'Index': index,                   'Dates': dts,                   'Benchmark': benchmark,                   'Portfolio': portfolio},                    columns = ['Index','Dates','Benchmark','Portfolio'])

Step 2: From "wide" to "long" format

df1 = pd.melt(df, id_vars=['Index','Dates']).sort_values(['variable','value'])df1    Index   Dates   variable    value9   48  2012-06-13  Benchmark   -1.4103011   93  2002-07-31  Benchmark   -1.3014898   97  2005-01-21  Benchmark   -1.1009850   67  2011-06-01  Benchmark   0.1265264   84  2003-09-25  Benchmark   0.4656453   18  2009-07-13  Benchmark   0.5227425   58  2007-12-04  Benchmark   0.7249157   98  2002-12-28  Benchmark   0.7465816   87  2009-02-07  Benchmark   1.4958272   99  2000-04-21  Benchmark   2.20742716  87  2009-02-07  Portfolio   -2.75022414  84  2003-09-25  Portfolio   -1.85563715  58  2007-12-04  Portfolio   -1.77945519  48  2012-06-13  Portfolio   -1.77413411  93  2002-07-31  Portfolio   -0.98486812  99  2000-04-21  Portfolio   -0.74856910  67  2011-06-01  Portfolio   -0.74765118  97  2005-01-21  Portfolio   -0.69598117  98  2002-12-28  Portfolio   -0.23415813  18  2009-07-13  Portfolio   0.240367

Step 3: Plot

sns.barplot(x='Dates', y='value', hue='variable', data=df1)plt.xticks(rotation=90)plt.ylabel('Returns')plt.title('Portfolio vs Benchmark Returns');