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Author: prabhupavitra

NumPyCodeFiles_Array Creation and Attributes.py

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+# Load the libraries
+import numpy as np
+
+
+# Creating arrays 
+# Method 1 : From a list/tuple
+arr_list = np.array([[[1,2,3,4],
+ [5,6,7,8],
+ [9,10,11,12]],
+ [[13,14,15,16],
+ [17,18,19,20],
+ [21,22,23,24]]],dtype="int32")
+
+print(f'Numpy array from a list :\n{arr_list}') 
+
+
+# Method 2 : From Built-in routines
+
+print(f"\n Using np.ones to create an array : \
+\n{np.ones((3,2),dtype=float)}") 
+
+print(f"\n Using np.zeros to create an array : \
+\n{np.zeros((4,3),dtype=int)}") 
+
+print(f"\n Using np.full to create an array : \
+\n{np.full((3,4,5),0.34)}") 
+
+# Uses numerical range built-in functions
+
+print(f'\n Using np.arange with step of 5 to create ndarray : \
+\n{np.arange(25,40,5)}')
+
+print(f'\n Using np.linspace with equally spaced elements to create ndarray : \
+\n{np.linspace(25,40,4)}')
+
+# Uses np.random 
+print(f'\n Using np.random.rand to create a uniform random array : \
+\n{np.random.rand(2,4)}')
+
+print(f'\n Using np.random.randn to create a normal random array : \
+\n{np.random.randn(2,4)}')
+
+print(f'\n Using np.random.normal to create a \
+random array of float in given interval : \
+\n{np.random.normal(-15,15,(2,3,4))}')
+
+print(f'\n Using np.random.randint to create a \
+random array of integers in given interval : \
+\n{np.random.randint(25,75,(2,3,4))}')
+
+# Uses np.eye
+print(f'\n Using np.eye to create a matrix with kth diagonal \
+elements set to 1 and others as 0: \
+\n{np.eye(4,k=1)}')
+
+
+
+
+# Loading files(txt,csv) to form numpy arrays 
+
+# 1. Using np.fromfile
+np.random.rand(2,10000).tofile("/Users/pavitragajanana/development/5. InternalFiles/randomtext")
+# Reading the file using fromfile
+randtext = np.fromfile("/Users/pavitragajanana/development/5. InternalFiles/randomtext")
+
+
+# 2. Using np.genfromtxt
+datafile_genfromtxt = np.genfromtxt("/Users/pavitragajanana/development/2. Data Files/CrudeOil_Daily_Cushing_OK_WTI_Spot_Price_FOB.csv",
+ usecols=[1],
+ delimiter=",",
+ skip_header=1)
+
+
+# 3. Loading csv files into numpy array using np.loadtxt
+datafile_arr = np.loadtxt("/Users/pavitragajanana/development/2. Data Files/CrudeOil_Daily_Cushing_OK_WTI_Spot_Price_FOB.csv",
+ delimiter=",",
+ skiprows=1, # Header
+ usecols=[1]) 
+
+
+# 4. Using csv library
+import csv
+from datetime import datetime
+
+with open("/Users/pavitragajanana/development/2. Data Files/CrudeOil_Daily_Cushing_OK_WTI_Spot_Price_FOB.csv", 'r') as f:
+ datafile = list(csv.reader(f, delimiter=","))
+
+# Converts the list to an ndarray
+datafile = np.array(datafile)
+# Converts into default datetime format
+datearray = np.array([datetime.strptime(x, "%m/%d/%y").strftime('%Y-%m-%d') for x in datafile[1:,0]])
+nominal = datafile[1:,1]
+
+# Recreates original array
+datafile = np.vstack([datearray,nominal]).T
+
+
+
+
+# Array Attributes (size,shape,ndim,nbytes,itemsize,dtype) 
+
+# We create a 1D, 2D and a 3D array to explore the attributes
+# One-Dimensional Array
+one_dim_array = np.random.randint(12, size=7)
+
+# Two-Dimensional Array
+two_dim_array = np.array([["Cupcake","Donut"],
+ ["Eclair","Froyo"],
+ ["Gingerbread","Honeycomb"],
+ ["Ice Cream Sandwich","Jelly Bean"],
+ ["KitKat","Lollipop"],
+ ["Marshmallow","Nougat"],
+ ["Oreo","Pie"]])
+
+# Three-Dimensional Array
+three_dim_array = np.array([[["Civic","Accord","Pilot","FR-V"],
+ ["Odyssey","Jazz","CR-V","NSX"]],
+ [["Insight","Ridgeline","Legend","HR-V"],
+ ["Passport","S660","Clarity","Mobilio"]],
+ [["Airwave","Avancier","Beat","Shuttle"],
+ ["Concerto","Element","Logo","Stream"]]])
+
+# Array Attributes for 1D array
+print(f'Dimensions of 1D array : {one_dim_array.ndim}')
+print(f'Size of 1D array : {one_dim_array.size}')
+print(f'Shape of 1D array : {one_dim_array.shape}')
+print(f'Total Bytes consumed by 1D array : {one_dim_array.nbytes}')
+print(f'dtype of 1D array : {one_dim_array.dtype}')
+print(f'Itemsize of 1D array : {one_dim_array.itemsize}')
+
+# Array Attributes for 2D array
+print(f'Dimensions of 2D array : {two_dim_array.ndim}')
+print(f'Size of 2D array : {two_dim_array.size}')
+print(f'Shape of 2D array : {two_dim_array.shape}')
+print(f'Total Bytes consumed by 2D array : {two_dim_array.nbytes}')
+print(f'dtype of 2D array : {two_dim_array.dtype}')
+print(f'Itemsize of 2D array : {two_dim_array.itemsize}')
+
+# Array Attributes for 3D array
+print(f'Dimensions of 3D array : {three_dim_array.ndim}')
+print(f'Size of 3D array : {three_dim_array.size}')
+print(f'Shape of 3D array : {three_dim_array.shape}')
+print(f'Total Bytes consumed by 3D array : {three_dim_array.nbytes}')
+print(f'dtype of 3D array : {three_dim_array.dtype}')
+print(f'Itemsize of 3D array : {three_dim_array.itemsize}')