data visulaisation Harpreet
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problem from contest
Home » Compete » CodeJunk » Zaikia and sticks Zaikia and sticks Problem Code: CKOJ20A Zaikia has N N sticks of distinct positive lengths A 1 , A 2 , … , A N A 1 , A 2 , … , A N . For no good reason at all, he wants to know if there is a triplet of sticks which when connected end-to-end will form a non-trivial triangle. Here non-trivial refers to a triangle with positive area. Help Zaikia know if such a triplet exists or not. If such a triplet exists, help him find the lexicographically largest applicable triplet . Input The first line contains an integer N N . The second line contains N N space-seperated integers A 1 , A 2 , … , A N A 1 , A 2 , … , A N . Output In the first line print YES if a triplet exists or NO if it doesn't. If such a triplet exists, then in the second line print the lexicographically largest applicable triplet . Con...
import and check version
test1 index import and check version 1. import and check version In [6]: import sys #access to system parameters https://docs.python.org/3/library/sys.html print ( "Python version: {} " . format ( sys . version )) import pandas as pd #collection of functions for data processing and analysis modeled after R dataframes with SQL like features print ( "pandas version: {} " . format ( pd . __version__ )) import matplotlib #collection of functions for scientific and publication-ready visualization print ( "matplotlib version: {} " . format ( matplotlib . __version__ )) import numpy as np #foundational package for scientific computing print ( "NumPy version: {} " . format ( np . __version__ )) import scipy as sp #collection of functions for scientific computing and advance mathematics print ( "SciPy version: {} " . ...
helpfull urls
Python: 1. learn python on kaggle Machine-learning: 1.A Data Science Framework: To Achieve 99% Accuracy | Kaggle Django: 1.django from scratch(documentation)
numpy , learn by jupyter screenshots (python for data science)
numpy
seaborn
seaborn-youtube In [16]: from IPython.display import Image from IPython.core.display import HTML from IPython.display import IFrame IFrame ( 'https://drive.google.com/file/d/11UVyiJ-JS2NHDurZuOpDNcZF6u1YGG1D/preview' , width = 640 , height = 480 ) # IFrame is a python code not markdown Out[16]: In [17]: IFrame ( 'https://indianaiproduction.com/artificial-intelligence/' , width = 640 , height = 480 ) Out[17]: In [ ]:
matplotlib starting concept
matplotlib-udemy-Copy1 In [1]: import matplotlib.pyplot as plt Matplotlib is building the font cache; this may take a moment. In [2]: % matplotlib inline In [4]: #plt.show() it is used (if you not using jupyter notebook) In [5]: import numpy as np x = np . linspace ( 0 , 5 , 11 ) y = x ** 2 In [6]: x Out[6]: array([0. , 0.5, 1. , 1.5, 2. , 2.5, 3. , 3.5, 4. , 4.5, 5. ]) In [7]: y Out[7]: array([ 0. , 0.25, 1. , 2.25, 4. , 6.25, 9. , 12.25, 16. , 20.25, 25. ]) In [8]: #functional plt . plot ( x , y ) Out[8]: [<matplotlib.lines.Line2D at 0x468f730>] In [9]: plt . plot ( x , y ) plt . show () # it is...
machine-learning-1-practical
machine-learning-1-practical In [4]: from IPython.display import Image from IPython.core.display import HTML from IPython.display import IFrame In [21]: import pandas as pd import matplotlib.pyplot as plt import numpy as np import os In [22]: pwd Out[22]: 'F:\\python for data science and machine learning\\machine-learning-1' In [41]: os . listdir ( 'F:/python for data science and machine learning/machine-learning-1' ) Out[41]: ['.ipynb_checkpoints', 'death .csv', 'machine-learning-1-practical.ipynb', 'screenshots'] In [48]: data = pd . read_csv ( 'death .csv' ) # attemtion death ke baad file me space tha phir csv isliye read nhi ho rhi thi data . head () Out[48]: ...
Creating a Basic Navigation using HTML CSS
code index.html <! DOCTYPE html > < html lang = "en" > < head > < meta charset = "UTF-8" /> < meta name = "viewport" content = "width=device-width, initial-scale=1.0" /> < link rel = "stylesheet" href = "style.css" /> < title > Document </ title > </ head > < body > < ul > < li class = "active" >< a href = "#" > Home </ a ></ li > < li >< a href = "#" > About Us </ a ></ li > < li >< a href = "#" > Services </ a ></ li > < li >< a...
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