from scipy.fftpack import fft, ifft
import numpy as np

x = np.array([1, 2, 4, 5])

x

array([1, 2, 4, 5])

y = fft(x)

y

array([12.+0.j, -3.+3.j, -2 …

def fib(n):
    if n == 0:
        return 0
    elif n == 1:
        return 1
    else:
        return fib(n-1) + fib(n-2)

print(fib(8))

21

print(fib(89))

import pyutil as pyu
pyu.get_local_pyinfo()

'conda env: ml311; pyv: 3.11.10 (main, Oct  3 2024, 07:29:13) [GCC 11.2.0]'

print(pyu.ps2("scipy"))

scipy==1.14.1

def get_fib(n):

    if n <= 1

    return 0

get_fib(5)

0

# 5 = 5 + 4 + 3 + 2 +1 = 

def …

def fibonacci(n):
    a = b = 1

    for i in range(n):
        yield a
        a, b = b, a+b

print(2)

2

for x in fibonacci(10):
    print(x)

1
1
2
3
5
8
13
21
34 …

def print_fibo(number):
    print(list(map(lambda x, f = lambda x, f : (f(x-1,f) + f(x-2,f)) if x > 1 else 1: f(x,f), range(number))))

print_fibo(6)

[1, 1, 2, 3 …

cmd = 'du -sh /tmp/datasets'
!{cmd}

 17M    /tmp/datasets

import gensim
from gensim import corpora
from gensim.utils import simple_preprocess
from smart_open import smart_open
import os

dictionary = corpora.Dictionary()

# Create gensim dictionary form a single tet file
dictionary = corpora.Dictionary(simple_preprocess(line, deacc=True …

import numpy as np
import pandas as pd

df = pd.read_csv('abc2.csv')

df

import numpy as np
import pandas as pd

datatype = [('Science', 'int32'), ('Maths', 'int32')]

current_values = np.zeros(3, dtype=datatype)

current_index = ['Row '+str(i) for i in range(1, 4)]

df = pd.DataFrame(current_values, index=current_index)

df

import numpy as np
import pandas as pd

df = pd.read_csv('marks.csv')

df