sakethramanujam

import math
import os
import json
import pandas as pd
import requests
from tqdm import tqdm
import os
import json
import tempfile
from datetime import datetime as dt

sakethramanujam

Installing libgfortran3 on ubuntu 20.04

Download the following debian packages either by navigating to the url or by doing a wget

• libgfortran3
• gcc-6-base

Post Download install the packages by using a software installer or using the

$ sudo dpkg -i 

sakethramanujam

import math
import pandas as pd
import numpy as np
from typing import List, Tuple, Union, Dict
from scipy.stats import skew, kurtosis
from .errors import StepSizeError, StepTypeError, SeriesError

class Statistics:
    """
    Methods to calculate statistics all or one at a time

sakethramanujam

series = [1,2,3,4,5]

stats = Statistics(series)
mean = stats.mean()
dev = stats.dev()

sakethramanujam

Keybase proof

I hereby claim:

• I am sakethramanujam on github.

• I am perceptiveproton (https://keybase.io/perceptiveproton) on keybase.

• I have a public key ASCuTkJ0KbN0EWGMZtesm1qkfdmLW5kXp8n8clZMHjMhKQo

sakethramanujam

import argparse
import re
from typing import Dict


def args():
    parser = argparse.ArgumentParser()
    parser.add_argument(
        '-f', '--file', help='Name of file to count words from')
    parser.add_argument('-n', '--N', help='Number of top items', type=int)

sakethramanujam

# !usr/bin/env python3
import requests                                                                                            
from bs4 import BeautifulSoup                                                                              


if __name__ == '__main__':
    url = 'https://www.who.int/countries/en/'                                                                  
    content = requests.get(url).content                                                                        
    soup = BeautifulSoup(content,'html5lib')                                                                   
    divs = soup.findAll('div', attrs={'class':'largebox'})                                                     

sakethramanujam

from matplotlib.lines import Line2D
from matplotlib.patches import Patch

def charmap(label):
    SUB = str.maketrans("0123456789", "₀₁₂₃₄₅₆₇₈₉")
    mu  = chr(956)
    sigma = chr(963)
    beta = chr(946)
    cmap = {'mean_x': mu+'$_{\ x}$','mean_y':mu+'$_{\ y}$','mean_sum': mu+'$_{\ I}$','mean_mag': mu+'$_{\ mag}$','mean_dir':mu+'$_{\ dir}$',
            'std_x':sigma+'$_{\ x}$','std_y':sigma+'$_{\ y}$','std_sum':sigma+'$_{\ I}$','std_mag':sigma+'$_{\ mag}$','std_dir':sigma+'$_{\ dir}$',

sakethramanujam

The above code can be used as follows

path_to_save_fi = 'your/path/'
save_importances(model,y_test.columns)

sakethramanujam

import pickle
def save_pickle(model):
    name=input('Name of the model: ')
    with open(f'{name}.pickle','wb') as model:
        pickle.dump(rf_model,model)
    print('Model Saved.')

def load_pickle(filename):
    file = open(filename,'rb')
    model = pickle.load(file)