颜色很重要，如果使用的好，就会帮助你突出数据的特征。
下面是使用seaborn的color palettes的一些例子，这些例子官网上面都已经有详细的介绍。
网址为：http://seaborn.pydata.org/tutorial/color_palettes.html#palette-tutorial
Drawing attractive figures is important. When making figures for yourself, as you explore a dataset, it’s nice to have plots that are pleasant to look at. Visualizations are also central to communicating quantitative insights to an audience, and in that setting it’s even more necessary to have figures that catch the attention and draw a viewer in.
import pandas as pd
import matplotlib.pyplot as plt
import pandas as pd
import matplotlib.pyplot as plt
import pandas as pd
reviews = pd.read_csv('fandango_scores.csv')
cols = ['FILM', 'RT_user_norm', 'Metacritic_user_nom', 'IMDB_norm', 'Fandango_Ratingvalue', 'Fandango_Stars']
norm_reviews = reviews[cols]
print(norm_reviews[:1])
import pandas as pd
unrate = pd.read_csv('UNRATE.csv')
unrate['DATE'] = pd.to_datetime(unrate['DATE'])
print(unrate.head(12))