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import numpy as np
np.random.seed(100)
X = np.random.random((10, 7)).round(3)
arr = np.genfromtxt("Datasets/Class_and_Fare.csv", delimiter=",", skip_header=1)
arr
import numpy as np
np.random.seed(100)
arr = np.random.normal(30, 10, 100).round(2)
arr
# Calc Profit
def calc_profit(open, high, low, close):
buy = open * 0.999
# daily range
if low < buy < high:
return (close - buy)/buy
else:
return 0
# Read Data
import numpy as np
np.set_printoptions(suppress=True)
data = np.genfromtxt("Datasets/Lifecyclesavings.csv", delimiter=",", skip_header=1)
data = data.round()
data[:10]
import numpy as np
# turn off scientific (e+02) notations.
np.set_printoptions(suppress=True)
# Create normal
np.random.seed(100)
arr = np.random.normal(100, 75, size=300).round(3)
arr
import numpy as np
arr = np. array([112, 118, 132, 129, 121, 135, 148, 148, 136, 119, 104, 118, 115,
126, 141, 135, 125, 149, 170, 170, 158, 133, 114, 140, 145, 150,
178, 163, 172, 178, 199, 199, 184, 162, 146, 166, 171, 180, 193,
181, 183, 218, 230, 242, 209, 191, 172, 194, 196, 196, 236, 235,
229, 243, 264, 272, 237, 211, 180, 201, 204, 188, 235, 227, 234,
264, 302, 293, 259, 229, 203, 229, 242, 233, 267, 269, 270, 315,
364, 347, 312, 274, 237, 278, 284, 277, 317, 313, 318, 374, 413,
405, 355, 306, 271, 306, 315, 301, 356, 348, 355, 422, 465, 467,
404, 347, 305, 336, 340, 318, 362, 348, 363, 435, 491, 505, 404,
import numpy as np
data = np.genfromtxt('Datasets/Mall_Customers_Int.csv',
delimiter=",",
skip_header=1)
# input
import pandas as pd
import numpy as np
ts = pd.Series(np.arange(20), pd.date_range('2001-01-01', periods=20, freq='2d'), name="values")
ts
# 1. Parse the following strings to datetime.
s1 = "2010 Jan 1"
s2 = '31-1-2000'
s3 = 'October10, 1996, 10:40pm'
# 2. How many days has it been between the end of first world war to the beginning of second world war?
"11 November 1918" to "1 september 1939"