From ca71f0b916bdd120d76864775098ac12dda56e90 Mon Sep 17 00:00:00 2001 From: chetanyb <95150398+chetanyb@users.noreply.github.com> Date: Wed, 6 Jul 2022 22:53:39 +0530 Subject: [PATCH] Codes I wrote in past days --- Chetany Bhardwaj/Day 1/merge_the_tools.py | 20 + .../Day 10/knn_classifier/car.data | 1729 +++++++++++++++++ .../Day 10/knn_classifier/main.py | 49 + Chetany Bhardwaj/Day 11/svm/main.py | 31 + .../Day 12/linear_regression/main.py | 36 + Chetany Bhardwaj/Day 2/max_it.py | 20 + .../Day 3/pythagorean_triples.cpp | 21 + Chetany Bhardwaj/Day 4/3sum_closure.cpp | 60 + .../Day 5/pythagorean_triples.cpp | 21 + Chetany Bhardwaj/Day 6/the_third_problem.cpp | 50 + Chetany Bhardwaj/Day 7/rain_chances.py | 14 + Chetany Bhardwaj/Day 9/fibonacci.py | 9 + 12 files changed, 2060 insertions(+) create mode 100644 Chetany Bhardwaj/Day 1/merge_the_tools.py create mode 100644 Chetany Bhardwaj/Day 10/knn_classifier/car.data create mode 100644 Chetany Bhardwaj/Day 10/knn_classifier/main.py create mode 100644 Chetany Bhardwaj/Day 11/svm/main.py create mode 100644 Chetany Bhardwaj/Day 12/linear_regression/main.py create mode 100644 Chetany Bhardwaj/Day 2/max_it.py create mode 100644 Chetany Bhardwaj/Day 3/pythagorean_triples.cpp create mode 100644 Chetany Bhardwaj/Day 4/3sum_closure.cpp create mode 100644 Chetany Bhardwaj/Day 5/pythagorean_triples.cpp create mode 100644 Chetany Bhardwaj/Day 6/the_third_problem.cpp create mode 100644 Chetany Bhardwaj/Day 7/rain_chances.py create mode 100644 Chetany Bhardwaj/Day 9/fibonacci.py diff --git a/Chetany Bhardwaj/Day 1/merge_the_tools.py b/Chetany Bhardwaj/Day 1/merge_the_tools.py new file mode 100644 index 0000000..315e254 --- /dev/null +++ b/Chetany Bhardwaj/Day 1/merge_the_tools.py @@ -0,0 +1,20 @@ +#Problem statement: https://www.hackerrank.com/challenges/merge-the-tools/problem +s = input("Enter the string: ") +lengthOfs = len(s) +k = int(input("Enter the value of k: ")) +if not lengthOfs%k == 0: + print("Entered value of k is not a factor of length of the string s\nExiting!") + exit() +numberOfSubstrings = int(lengthOfs/k) +referenceNumber = 0 +substring = [] +finalSubstring = [] +for i in range(0,numberOfSubstrings): + substring.append(s[referenceNumber:referenceNumber+k]) + for character in substring[i]: + print(character) + finalSubstring.append("") + if character not in finalSubstring[i]: + finalSubstring[i]=finalSubstring[i]+character + referenceNumber+=k + print(f"{i}:{finalSubstring[i]}") \ No newline at end of file diff --git a/Chetany Bhardwaj/Day 10/knn_classifier/car.data b/Chetany Bhardwaj/Day 10/knn_classifier/car.data new file mode 100644 index 0000000..6ec6bd8 --- /dev/null +++ b/Chetany Bhardwaj/Day 10/knn_classifier/car.data @@ -0,0 +1,1729 @@ +buying,maint,doors,persons,lug_boot,safety,class +vhigh,vhigh,2,2,small,low,unacc +vhigh,vhigh,2,2,small,med,unacc +vhigh,vhigh,2,2,small,high,unacc +vhigh,vhigh,2,2,med,low,unacc +vhigh,vhigh,2,2,med,med,unacc +vhigh,vhigh,2,2,med,high,unacc 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+low,low,5more,more,big,med,good +low,low,5more,more,big,high,vgood diff --git a/Chetany Bhardwaj/Day 10/knn_classifier/main.py b/Chetany Bhardwaj/Day 10/knn_classifier/main.py new file mode 100644 index 0000000..9222ce2 --- /dev/null +++ b/Chetany Bhardwaj/Day 10/knn_classifier/main.py @@ -0,0 +1,49 @@ +import numpy as np +import pandas as pd +from sklearn import neighbors, metrics +from sklearn.model_selection import train_test_split +from sklearn.preprocessing import LabelEncoder + +data = pd.read_csv('D:\Codes\Python codes\scikit_learn\knn_classifier\car.data') +#print(data.head()) + +X = data[[ + 'buying', + 'maint', + 'safety' +]].values +Y = data[['class']] +#print(X,Y) + +#converting string data to machine readable form +#X +Le = LabelEncoder() +for i in range(len(X[0])): + X[:, i] = Le.fit_transform(X[:, i]) +#print(X) + +#converting string data to machine readable form/method 2 +#Y +label_mapping = { + 'unacc':0, + 'acc':1, + 'good':2, + 'vgood':3 +} +Y['class'] = Y['class'].map(label_mapping) +Y = np.array(Y) +#print(Y) + +#creating model + +knn = neighbors.KNeighborsClassifier(n_neighbors=25, weights='uniform') +X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2) +knn.fit(X_train, Y_train) +prediction = knn.predict(X_test) +accuracy = metrics.accuracy_score(Y_test, prediction) +print('predictions: ', prediction) +print('accuracy: ', accuracy) + +a = 15 +print('actual value: ', Y[a]) +print('predicted value: ', knn.predict(X)[a]) \ No newline at end of file diff --git a/Chetany Bhardwaj/Day 11/svm/main.py b/Chetany Bhardwaj/Day 11/svm/main.py new file mode 100644 index 0000000..4673a70 --- /dev/null +++ b/Chetany Bhardwaj/Day 11/svm/main.py @@ -0,0 +1,31 @@ +from sklearn import datasets +import numpy as np +from sklearn.model_selection import train_test_split +from sklearn import svm +iris = datasets.load_iris() +from sklearn.metrics import accuracy_score +#splitting in features and labels +X = iris.data +Y = iris.target + +#creating a list to keep track of all the possible classes +classes = ['Iris Setosa', 'Iris Versicolour', 'Iris Virginica'] + +print(X.shape) +print(Y.shape) + +X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2) + +model = svm.SVC() +model.fit(X_train, Y_train) +print(model) + +predictions = model.predict(X_test) +accuracy = accuracy_score(Y_test, predictions) + +print('predictions: ', predictions) +print('actual: ', Y_test) +print('accuracy: ', accuracy) + +for i in range(len(predictions)): + print(classes[predictions[i]]) \ No newline at end of file diff --git a/Chetany Bhardwaj/Day 12/linear_regression/main.py b/Chetany Bhardwaj/Day 12/linear_regression/main.py new file mode 100644 index 0000000..d4dcbbd --- /dev/null +++ b/Chetany Bhardwaj/Day 12/linear_regression/main.py @@ -0,0 +1,36 @@ +from statistics import linear_regression +from sklearn import datasets +from sklearn import linear_model +from sklearn.model_selection import train_test_split +from matplotlib import pyplot as plt + +boston = datasets.load_boston() + +#splitting into features and labels +X = boston.data +Y = boston.target + +#print("X") +#print(X) +#print(X.shape) +#print("Y") +#print(Y) +#print(Y.shape) + +#algorithm +l_reg = linear_model.LinearRegression() + +#visualising the data +plt.scatter(X.T[5], Y) +plt.show() + +#train test split +X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2) + +#training +model = l_reg.fit(X_train, Y_train) +predictions = model.predict(X_test) +print('Predictions: ', predictions) +print('R^2 value: ', l_reg.score(X, Y)) +print("Coefficient: ", l_reg.coef_) +print("Intercept: ", l_reg.intercept_) \ No newline at end of file diff --git a/Chetany Bhardwaj/Day 2/max_it.py b/Chetany Bhardwaj/Day 2/max_it.py new file mode 100644 index 0000000..6657445 --- /dev/null +++ b/Chetany Bhardwaj/Day 2/max_it.py @@ -0,0 +1,20 @@ +#Problem statement: https://www.hackerrank.com/challenges/angry-children/problem +import itertools +K , M = input() +k = int(K) +m = int(M) +Lis = list() +S = 0 +k = 0 +for i in range(k): + l = list(map(int , input().strip().split(' '))) + n = l[0] + Lis.append(l[1:]) + assert len(Lis[i]) == n + +for l in itertools.product(*Lis): + s = sum([x**2 for x in l])%m + if s>S: + S = s + k = l +print(S) \ No newline at end of file diff --git a/Chetany Bhardwaj/Day 3/pythagorean_triples.cpp b/Chetany Bhardwaj/Day 3/pythagorean_triples.cpp new file mode 100644 index 0000000..7b73ec2 --- /dev/null +++ b/Chetany Bhardwaj/Day 3/pythagorean_triples.cpp @@ -0,0 +1,21 @@ +//Problem statement: https://codeforces.com/contest/1487/problem/D +#include +using namespace std; +#define ll long long +#define ull unsigned long long + +int main(){ + int t ; + cin>>t; + while(t--){ + ll n ; + cin>>n; + ll count = 0 ; + ll a , b , c; + for(int i = 3 ; i*i <= 2*n - 1;i+=2){ + count++; + } + cout< +using namespace std; +#define ll long long +#define ull unsigned long long + +int main(){ + int t ; + cin>>t ; + while(t--){ + ll n ; + cin>>n; + map m; + vector v ; + ll a[n] , z = 0 ; + for(ll i = 0 ; i < n ;i++){ + cin>>a[i]; + if(a[i]==0){ + z++; + } + m[a[i]]++; + if(m[a[i]]<=3){ + v.push_back(a[i]); + } + } + + if (z==n){ + cout<<"YES"<10){ + cout << "NO" << endl; + } + else{ + ll l = v.size(); + bool t = true; + for(int i = 0 ; i< l ; ++i){ + for(int j = i+1 ; j +using namespace std; +#define ll long long +#define ull unsigned long long + +int main(){ + int t ; + cin>>t; + while(t--){ + ll n ; + cin>>n; + ll count = 0 ; + ll a , b , c; + for(int i = 3 ; i*i <= 2*n - 1;i+=2){ + count++; + } + cout< +using namespace std; +#define ll long long + +const ll N= 1e5; + +const ll mod = 1e9+7; + +ll p[N], mn, mx; + +ll ans; +ll solve(ll a[] , ll n){ + + ans=1; + + for (ll i=0;imx) { + mx =p[i]; + } + else if(p[i]>t ; + while(t--){ + ll n ; + cin>>n; + ll a[n] ; + for(ll i = 0 ;i< n ;i++){ + cin>>a[i]; + } + ll ans = solve(a , n); + cout<