hute37

#!/bin/bash

# This installs alacritty terminal on ubuntu (https://github.com/jwilm/alacritty)
# You have to have rust/cargo installed for this to work

# Install required tools
sudo apt-get install -y cmake libfreetype6-dev libfontconfig1-dev xclip

# Download, compile and install Alacritty
git clone https://github.com/jwilm/alacritty

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VIM KEYBOARD SHORTCUTS

MOVEMENT

h        -   Move left
j        -   Move down
k        -   Move up
l        -   Move right
$        -   Move to end of line
0        -   Move to beginning of line (including whitespace)

hute37

#!/bin/bash
#If no argument is specified, ask for it and exit
if [[ -z "$@" ]];
then
    echo "An argument is needed to run this script";
    exit
else
    arg="$@"
    #Basic check to make sure argument number is valid. If not, display error and exit
    if [[ $(($(echo $arg | grep -o "\s" | wc --chars) / 2 )) -ne 2 ]];

hute37

<?php # -*- coding: utf-8 -*-
declare( strict_types = 1 ); 
/**
 * Plugin Name: Port Switch
 * Plugin URI:  https://gist.github.com/bueltge/51013ab809f5f0f5e305c70c2d393fff
 * Description: Port switch to get an workaround to use WordPress Multisite also without the default port 80.
 * Version:     dev
 * Author:      Frank Bültge
 * Author URI:  https://bueltge.de
 * License:     MIT

hute37

#different aggregate functions
table = pd.pivot_table(df,index=['Sex','Pclass'],aggfunc={'Age':np.mean,'Survived':np.sum})
table

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df.groupby(['Outlet_Type','Item_Type']).agg(mean_MRP=('Item_MRP',np.mean),mean_Sales=('Item_Outlet_Sales',np.mean))

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df['Item_Weight'] = df.groupby(['Item_Fat_Content','Item_Type'])['Item_Weight'].transform(lambda x: x.fillna(x.mean()))

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def filter_func(x):
    return x['Item_Weight'].std() < 3

df_filter = df.groupby(['Item_Weight']).filter(filter_func)
df_filter.shape

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#displays the subtotal using margins and margins_name

# margins is a boolean field that should be made True if total values need to be printed.

# margins_name is the optional field where you can name the margin row/column in your grouped table.

table = pd.pivot_table(df,index=['Sex'],columns=['Pclass'],values=['Survived'],aggfunc=np.sum, margins=True, margins_name='Total_Survived')
table

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import time
def fibonacci_sequence_of(num):
	first_number = 0
	second_number = 1
	num = int(num)
	if num == 0:
		print ("Fibonacci of {} is {}".format(num,num))
	elif num ==1:
		print ("Fibonacci of {} is {}".format(num,num))
	else: