Exploratory Data Analysis¶

[1]:

import sys
ppath = "../.."

if ppath not in sys.path:
    sys.path.append(ppath)

import pygeostatistics as pygs

[2]:

data = pygs.gslib_reader.SpatialData('../../testData/test.gslib')

[3]:

data.mean

[3]:

14.695879999999999

[4]:

print(data.summary)

Summary
-------
Number of Data: 85
Mean: 14.695879999999999
Variance: 0.7868342092380952
Minimum: 12.1491
Lower Quartile: 14.1333
Median: 14.6515
Upper Quartile: 15.2606
Maximum: 16.9583

[5]:

import matplotlib.pyplot as plt
%matplotlib notebook
fig, ax = plt.subplots()
data.pdf(ax)

[8]:

type(ax)

[8]:

matplotlib.axes._subplots.AxesSubplot

[9]:

type(ax3d)

[9]:

matplotlib.axes._subplots.Axes3DSubplot

[6]:

from mpl_toolkits.mplot3d import Axes3D

[7]:

fig3d = plt.figure()
ax3d = fig3d.add_subplot(111, projection='3d')
sc = data.scatter(ax3d)
fig3d.colorbar(sc)

[7]:

<matplotlib.colorbar.Colorbar at 0x2d3cbda6668>