Given the names and grades for each student in a class N of students, store them in a nested list and print the name(s) of any student(s) having the second lowest grade.

Overview

Hackerank-Nested-List

Given the names and grades for each student in a class N of students, store them in a nested list and print the name(s) of any student(s) having the second lowest grade.

  scorex=[]
  namex=[]
  for _ in range(int(raw_input())):
      name = raw_input()
      score = float(raw_input())
      scorex.append(score)
      namex.append(name)

  i = min(scorex)
  flag = True
  while flag:
      if i in scorex:
          namex.pop(scorex.index(i))
          scorex.pop(scorex.index(i))
      else:
          flag=False
  t=min(scorex)
  names=[]
  flag=True

  count =scorex.count(t)

  for _ in range (count):
      names.append(namex[scorex.index(t)])
      namex.pop(scorex.index(t))
      scorex.pop(scorex.index(t))
  names.sort()
  for i in names:
      print i
Owner
Sangeeth Mathew John
Bachelor of Technology
Sangeeth Mathew John
PySpark + Scikit-learn = Sparkit-learn

Sparkit-learn PySpark + Scikit-learn = Sparkit-learn GitHub: https://github.com/lensacom/sparkit-learn About Sparkit-learn aims to provide scikit-lear

Lensa 1.1k Jan 04, 2023
Predict profitability of trades based on indicator buy / sell signals

Predict profitability of trades based on indicator buy / sell signals Trade profitability analysis for trades based on various indicators signals: MAC

Tomasz Porzycki 1 Dec 15, 2021
A scikit-learn based module for multi-label et. al. classification

scikit-multilearn scikit-multilearn is a Python module capable of performing multi-label learning tasks. It is built on-top of various scientific Pyth

802 Jan 01, 2023
Predico Disease Prediction system based on symptoms provided by patient- using Python-Django & Machine Learning

Predico Disease Prediction system based on symptoms provided by patient- using Python-Django & Machine Learning

Felix Daudi 1 Jan 06, 2022
Time Series Prediction with tf.contrib.timeseries

TensorFlow-Time-Series-Examples Additional examples for TensorFlow Time Series(TFTS). Read a Time Series with TFTS From a Numpy Array: See "test_input

Zhiyuan He 476 Nov 17, 2022
MiniTorch - a diy teaching library for machine learning engineers

This repo is the full student code for minitorch. It is designed as a single repo that can be completed part by part following the guide book. It uses

1.1k Jan 07, 2023
A Python implementation of FastDTW

fastdtw Python implementation of FastDTW [1], which is an approximate Dynamic Time Warping (DTW) algorithm that provides optimal or near-optimal align

tanitter 651 Jan 04, 2023
李航《统计学习方法》复现

本项目复现李航《统计学习方法》每一章节的算法 特点: 笔记摘要:在每个文件开头都会有一些核心的摘要 pythonic:这里会用尽可能规范的方式来实现,包括编程风格几乎严格按照PEP8 循序渐进:前期的算法会更list的方式来做计算,可读性比较强,后期几乎完全为numpy.array的计算,并且辅助详

58 Oct 22, 2021
Python Research Framework

Python Research Framework

EleutherAI 106 Dec 13, 2022
vortex particles for simulating smoke in 2d

vortex-particles-method-2d vortex particles for simulating smoke in 2d -vortexparticles_s

12 Aug 23, 2022
A Python implementation of GRAIL, a generic framework to learn compact time series representations.

GRAIL A Python implementation of GRAIL, a generic framework to learn compact time series representations. Requirements Python 3.6+ numpy scipy tslearn

3 Nov 24, 2021
Combines MLflow with a database (PostgreSQL) and a reverse proxy (NGINX) into a multi-container Docker application

Combines MLflow with a database (PostgreSQL) and a reverse proxy (NGINX) into a multi-container Docker application (with docker-compose).

Philip May 2 Dec 03, 2021
Client - 🔥 A tool for visualizing and tracking your machine learning experiments

Weights and Biases Use W&B to build better models faster. Track and visualize all the pieces of your machine learning pipeline, from datasets to produ

Weights & Biases 5.2k Jan 03, 2023
GroundSeg Clustering Optimized Kdtree

ground seg and clustering based on kitti velodyne data, and a additional optimized kdtree for knn and radius nn search

2 Dec 02, 2021
Sleep stages are classified with the help of ML. We have used 4 different ML algorithms (SVM, KNN, RF, NN) to demonstrate them

Sleep stages are classified with the help of ML. We have used 4 different ML algorithms (SVM, KNN, RF, NN) to demonstrate them.

Anirudh Edpuganti 3 Apr 03, 2022
Responsible AI Workshop: a series of tutorials & walkthroughs to illustrate how put responsible AI into practice

Responsible AI Workshop Responsible innovation is top of mind. As such, the tech industry as well as a growing number of organizations of all kinds in

Microsoft 9 Sep 14, 2022
A machine learning web application for binary classification using streamlit

Machine Learning web App This is a machine learning web application for binary classification using streamlit options this application contains 3 clas

abdelhak mokri 1 Dec 20, 2021
BigDL: Distributed Deep Learning Framework for Apache Spark

BigDL: Distributed Deep Learning on Apache Spark What is BigDL? BigDL is a distributed deep learning library for Apache Spark; with BigDL, users can w

4.1k Jan 09, 2023
Backtesting an algorithmic trading strategy using Machine Learning and Sentiment Analysis.

Trading Tesla with Machine Learning and Sentiment Analysis An interactive program to train a Random Forest Classifier to predict Tesla daily prices us

Renato Votto 31 Nov 17, 2022