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 = normal_movies, x="Profitable",y ="Audience Rating",ax = ax1)
sns.boxplot(data = normal_movies, x="Profitable",y ="Critic Rating",ax = ax2)
