python pandas plotting tools

plotting tools

1. scatter matrix plot

2. desity plot

3. andrews curves

4. parallel coordinates

5. lag plot

6. autocorrelation plot

7. bootstrap plot

8. radviz

code

• import code

        import matplotlib.pyplot as plt
        import matplotlib
        matplotlib.style.use('ggplot')
        import numpy as np
        import pandas as pd
        %matplotlib inline
  

1. scatter matrix plot

        from pandas.tools.plotting import scatter_matrix
        df = pd.DataFrame(np.random.randn(1000, 4),
                          columns=['a', 'b', 'c', 'd'])
        scatter_matrix(df, alpha=0.2, figsize=(6, 6), diagonal='kde')
   

2. desity plot

        ser = pd.Series(np.random.randn(1000))
        ser.plot(kind='kde')
   

3. andrews curves

        from pandas import read_csv
        from pandas.tools.plotting import andrews_curves
        data = pd.read_csv('iris.data')
        plt.figure()
        andrews_curves(data, 'Name')
   

4. parallel coordinates

        from pandas import read_csv
        from pandas.tools.plotting import parallel_coordinates
        data = read_csv('iris.data')
        plt.figure()
        parallel_coordinates(data, 'Name')
   

5. lag plot

        from pandas.tools.plotting import lag_plot
        plt.figure()
        data = pd.Series(0.1 * np.random.rand(1000) +
                         0.9 * np.sin(np.linspace(-99 * np.pi, 99 * np.pi, num=1000)))
        lag_plot(data)
   

6. autocorrelation plot

        from pandas.tools.plotting import autocorrelation_plot
        plt.figure()
        data = pd.Series(0.7 * np.random.rand(1000) +
                         0.3 * np.sin(np.linspace(-9 * np.pi, 9 * np.pi, num=1000)))
        autocorrelation_plot(data)
   

7. bootstrap plot

        from pandas.tools.plotting import bootstrap_plot
        data = pd.Series(np.random.rand(1000))
        bootstrap_plot(data, size=50, samples=500, color='grey')
   

8. radviz

        from pandas import read_csv
        from pandas.tools.plotting import radviz
        data = read_csv('iris.data')
        plt.figure()
        radviz(data, 'Name')