jerilkuriakose

# Used to clean and analyse the data-set
import pandas as pd
# To open an excel file
df = pd.ExcelFile('myexcel.xls').parse('Sheet1')

jerilkuriakose

import scipy
import matplotlib.pyplot as plt
import scipy.cluster.hierarchy as sch
# %matplotlib inline
# uncomment the above line if using Jupyter notebook

# creating dummy variable for plotting
# 'D' is a 2-d array that has our data
# for demonstartion purpose we are creating random variables
x = scipy.rand(40)

jerilkuriakose

# Using our context manager
with OpenHDFS(filename) as store:
    store.put('d1', df)

jerilkuriakose

from pandas import DataFrame
# import the required library to open HDF file
from pandas import HDFStore

# File that stores the dataframe
filename = 'data.h5'
# Creating a dataframe
df = DataFrame(np.random.randn(5,3), columns=['A', 'B', 'C',])

class OpenHDFS():

jerilkuriakose

a = 25

jerilkuriakose

jerilkuriakose

jerilkuriakose

#coding:utf-8
import psutil
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation

TIME_NUM = 90
FRAMES = 360

jerilkuriakose

#!/bin/bash
dbus-send --system --print-reply --dest=org.freedesktop.login1 /org/freedesktop/login1 "org.freedesktop.login1.Manager.Suspend" boolean:true

jerilkuriakose

# import the required library to open HDF file
from pandas import HDFStore

class OpenHDFS():
    """
    Context Manager class to open / create a HDFS / h5 file
    """

    def __init__(self, filename):
        """