kaskichandrakant

function sort(list) {
  if (list.length == 1) {
    return list;
  }
  var listA = sort(list.slice(0, list.length / 2))
  var listB = sort(list.slice(list.length / 2))
  var indexA = 0
  var indexB = 0
  var newList = []
  while (indexA < listA.length || indexB < listB.length) {

kaskichandrakant

#!/bin/bash

if [ "$1" == "." ]; then
    REPO_NAME=$(basename $PWD)
    echo "creating $REPO_NAME repo on github"
    git init .
    curl -u "$(git config  user.name)" https://api.github.com/user/repos -d '{"name":"'$REPO_NAME'"}'
  elif [[ $# -gt 0  && "$1" != "-h" ]]; then
    echo "creating $1 repo on github"
    curl -u "$(git config  user.name)" https://api.github.com/user/repos -d '{"name":"'$1'"}'

kaskichandrakant

#!/bin/sh
echo "Running SwiftLint"
cd Sto
FILE_NAME=$(basename $PWD)
echo "running swiftlint in  $FILE_NAME"
Swiftlint --strict
if [ $? != 0 ] ; then
    echo "swiftlint failed make required changes to your code"
    exit 1
fi

kaskichandrakant

(defn addition_of_numbers [array]
  (reduce + array))
;--------------------------------------
(defn added_num_at_start [array num]
  (cons num array))
;--------------------------------------
(defn calculated_value [operation num1 num2]
  (cond-> num1
    (= "add" operation) (+ num2)
    (= "sub" operation) (- num2)

kaskichandrakant

(refer 'clojure.set :only '[rename-keys])
(require '[clojure.string :as str])

; -------------------Creating the map---------------
(def person {:name "any" :age 12})
(:name person)
(:age person)

(def train {:engine "train Engine" :containers ["first" "second" "third"]})
(:containers train)

kaskichandrakant

import IPython
name = 'my_python'
#define functions
def my_fun():
    print('do something')
IPython.embed()

kaskichandrakant

df.apply(lambda x: x.str.strip)
df.loc[df["column_name"] == "value", "column_to_changed"] = 'new_value'
df.reanme(columns={'old_column_name':'new_colmn_name'})
df['column_name'].fillna('value',inplace=True)

kaskichandrakant

from astropy.io import fits
import sys

import matplotlib.pyplot as plt
data = fits.open(str(sys.argv[1]))[0].data

plt.imshow(data[0][0])
plt.show()

kaskichandrakant

import pandas as pd
from sklearn import tree,model_selection
df = pd.read_csv('path/to/csv')

target = df["target_column_name"].values
feature_names = ['columns','with','which','decision','is','to','be','made']

features = df[feature_names].values

visual_tree = tree.DecisionTreeClassifier(random_state=1

kaskichandrakant

let collector = function(collection){return (unit)=>{collection.push(unit)}}
let collectionA = []
collectorForA=collector(collectionA)
collectorForA(1)