Detailed explanation of DataFrame.plot function (5)

The fifth part mainly introduces the df.scatter, df.box and df.boxplot drawing functions, scatter plots and box plot examples. The scatter plot controls the size of the scatter points through the s parameter, and the colormap can display gradient colors.

1. scatter

DataFrame.plot.scatter(x, y, s=None, c=None, **kwargs)
c: is the color of each point, which can be a value or an array value
s: is the size of each point, Can be a value or an array value

df = pd.DataFrame([[5.1, 3.5, 0], [4.9, 3.0, 0], [7.0, 3.2, 1],
                   [6.4, 3.2, 1], [5.9, 3.0, 2]],
                  columns=['length', 'width', 'species'])
ax1 = df.plot.scatter(x='length',
                      y='width',
                      c='Blue',marker='H',figsize=(3,3),fontsize=12,title='Scatter')

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ax2 = df.plot.scatter(x='length',
                      y='width',
                      c='species',marker='H',figsize=(3,3),fontsize=12,title='Scatter',
                      colormap='viridis')

c is a list, which displays the size of the value through colormap. Scatter can represent three-dimensional data.

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ax2 = df.plot.scatter(x='length',
                      y='width',
                      s=df['species']*100,marker='H',figsize=(3,3),fontsize=12,title='Scatter')

s=df['species']*100, because the value is relatively small, the magnification factor, the size of the hexagon.

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2. box

DataFrame.plot.box(by=None, **kwargs)

data = np.random.randn(25, 4)
df = pd.DataFrame(data, columns=list('ABCD'))
ax = df.plot.box(figsize=(3,3),title='Box')

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age_list = [8, 10, 12, 14, 72, 74, 76, 78, 20, 25, 30, 35, 60, 85]
df = pd.DataFrame({"gender": list("MMMMMMMMFFFFFF"), "age": age_list})
ax = df.plot.box(column="age", by="gender", figsize=(3, 2))

by="gender", statistics by gender

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3. boxplot

DataFrame.boxplot(column=None, by=None, ax=None, fontsize=None, rot=0, grid=True, figsize=None, layout=None, return_type=None, backend=None, **kwargs)

np.random.seed(1234)
df = pd.DataFrame(np.random.randn(10, 4),columns=['Col1', 'Col2', 'Col3', 'Col4'])
boxplot = df.boxplot(column=['Col1', 'Col2', 'Col3'],color='b')

Specify to display 3 columns of data, the effect is as follows:
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df = pd.DataFrame(np.random.randn(10, 2),columns=['Col1', 'Col2'])
df['X'] = pd.Series(['A', 'A', 'A', 'A', 'A','B', 'B', 'B', 'B', 'B'])
boxplot = df.boxplot(by='X',color='b',figsize=(6,4))
plt.show()

by='X', display according to X classification

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