1. If we create a DataFrame, each of the column inside of it is already a set of Series. Does not necessary to change them into a one-column Dataframe.

2. Here we use scatter_matrix function to plot the DataFrame:

　　normal_movies = hollywood_movies[hollywood_movies["Film"] != "Paranormal Activity"]

　　from pandas.tools.plotting import scatter_matrix #import scatter_matrix function from pandas.tool.plotting

　　scatter_matrix(normal_movies[["Profitability","Audience Rating"]],figsize = (6,6)) #If we only put two columns into the scatter_matrix, we will get 4 plotting inside of the figure. it is a vs a, a vs b, b vs a, b vs b. a = "Profitability",     b = "Audience Rating".

3. In the following code, we plot cirtic rating and audience rating compare to a range which is generate automatically.

　　normal_movies[["Critic Rating","Audience Rating"]].plot(kind = "box")

4.While we use seaborn.boxplot function, here is the example.

　　normal_movies = normal_movies.sort_values("Year")

　　fig = plt.figure(figsize=(8,4))

　　yr1 = fig.add_subplot(1,2,1)
　　yr2 = fig.add_subplot(1,2,2)

　　sns.boxplot(x=normal_movies["Year"], y=normal_movies["Critic Rating"],ax = yr1)
　　sns.boxplot(x=normal_movies["Year"], y=normal_movies["Audience Rating"],ax = yr2)
　　plt.show()

output:

5. 

 Another way of using boxplot:

　　normal_movies[‘Profitable‘]= normal_movies["Profitability"] >= 1
　　fig = plt.figure(figsize = (12,6))
　　ax1 = fig.add_subplot(1,2,1)
　　ax2 = fig.add_subplot(1,2,2)
　　sns.boxplot(data = http://www.mamicode.com/normal_movies, x="Profitable",y ="Audience Rating",ax = ax1)
　　sns.boxplot(data = http://www.mamicode.com/normal_movies, x="Profitable",y ="Critic Rating",ax = ax2)

Data Visualizations 7