Python info Examples

Example #1

File: helpInfoSource.py Project: ArpanMahatra1999/Scipy

from scipy import cluster
import scipy

help(cluster)
scipy.info(cluster)
scipy.source(cluster)

Example #2

File: sp_misc.py Project: netflow0/20190506Bettis

def main():
    print(sp.info(cs_diff))
    print('-' * 60)
    print(sp.source(cs_diff))

Example #3

File: Ex 1.3.6 Statistics.py Project: aysla001/ExploreDataScience

import numpy as np
import scipy as sp

from scipy import stats
data = np.genfromtxt('iris.data', delimiter=',', dtype='f8,f8,f8,f8,S15',names=['sepal_length', 'sepal_width', 'petal_length', 'petal_width', 'type_string'])
sizeofdata, (minval,maxval), mean, variance, skew, kurtosis = stats.describe(data['petal_width'])

#provides further info of what the stats above are returning
sp.info(stats.describe)

#returns max and other data stats on petal_length
stats.describe(data['petal_length'])
# returns (150, (1.0, 6.9000000000000004), 3.7586666666666693, 3.1131794183445156, -0.2717119501716454, -1.395359302139705)

#median is not provided can be found using sp.median
sp.median(data['petal_length'])

Example #4

File: scipy.py Project: schottkey7/explore-data-science-metis

import scipy as sp
import numpy as np
from scipy import stats

# help
help(open)
sp.info("mean")
sp.info(sp.mean)


data = np.genfromtxt(
    'iris.data',
    delimiter=',',
    dtype='f8,f8,f8,f8,S15',
    names=['sepal_length', 'sepal_width', 'petal_length', 'petal_width', 'type_string']
)

sizeofdata, (minval,maxval), mean, variance, skew, kurtosis = stats.describe(data['petal_width'])
sp.median(data['petal_length'])

Example #5

File: scipy1.py Project: pnayak1501/MachineLearning-practice

import scipy as sp
from scipy import integrate
from scipy import cluster
from scipy import fftpack

# help(integrate)
sp.info(fftpack)            #To get info about any sub-package
sp.source(cluster)          #To get the source code of any subpackage

Example #6

import numpy as np
import scipy as sp
import matplotlib as mpl
import matplotlib.pyplot as plt

from scipy import linalg, optimize

print sp.info(optimize.fmin)