plot1 = sns.catplot(y="Track",
                 x="Score",
                 data=test_scores, 
                 jitter=True, 
                 height=9, 
                 aspect=0.5,
                 kind = "violin", 
                 col = "Complexity",
                 cut = 0,
                 col_order = ["Easy","Medium","Difficult"],
                 palette = sns.color_palette(["#a05195","#d45087","#f95d6a"])) \
                .set_ylabels(fontsize=25) \
                .set_xlabels(fontsize = 25, label = "Score") \
                .set_xticklabels(fontsize=20) \
                .set_yticklabels(fontsize=20) \
                .set_titles(size = 20) 

plot1.fig.subplots_adjust(top=0.8)
plot1.fig.suptitle('Violin Plot showing distribution of score for each track by complexity',size = 30)
#plot1.savefig("Violin Plot -1.png",dpi=100,bbox_inches='tight')

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import matplotlib.pylab as plb
import warnings
warnings.filterwarnings('ignore')

test_scores = pd.read_csv("Data/Test scores.csv", parse_dates=['Test taken date'])
test_master = pd.read_csv("Data/Test master.csv")
test_participant = pd.read_csv("Data/Audience summary.csv")

test_scores.head()