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Die Macher des legendären „Duke Nukem 3D“ legen 23 Jahre später mit „Ion Fury“ eine furiose Portion Nostalgie nach - leider mit Altlasten. Auf Facebook teilen Auf Twitter teilen Von Rainer Sigl Die Neunzigerjahre sind längst wieder da, zumindest in Sachen First-Person-Shooter. In den letzten Monaten hat sich eine ganze Reihe famoser Indie-Titel der knallharten, geradlinigen Shooter-Vergangenheit wieder angenommen. Jetzt steht aber statt lauwarmer Erinnerungskost sozusagen ein Original wieder ...

Sets Symmetric Difference Task Given sets of integers, and , print their symmetric difference in ascending order. The term symmetric difference indicates those values that exist in either or but do not exist in both. Input Format The first line of input contains an integer, . The second line contains space-separated integers. The third line contains an integer, . The fourth line contains space-separated integers. Output Format Output the symmetric difference integers in ascending...

itertools.permutations() itertools.permutations(iterable[, r]) This tool returns successive length permutations of elements in an iterable. If is not specified or is None, then defaults to the length of the iterable, and all possible full length permutations are generated. Permutations are printed in a lexicographic sorted order. So, if the input iterable is sorted, the permutation tuples will be produced in a sorted order. My solution from itertools import permutations inp = input().spli...

cmath cmath.phase This tool returns the phase of complex number z (also known as the argument of z). >>>phase(complex(-1.0, 0.0)) 3.1415926535897931 ## cmath.abs This tool returns the modulus (absolute value) of complex number z. You are given a complex . Your task is to convert it to polar coordinates. My solution Adapted solution code cmath.polar() Task You are given a complex number z . Your task is to convert it to polar coordinates. Input Format A single line containi...

C3-4: Pandas L1: Anaconda L2: Jupyter Notebooks L3: NumPy L4: Pandas Creating Pandas Series import pandas as pd | Import Pandas my_series = pd.Series(data = ['data1', 'data2', data3', 'data4'], index = ['row1', 'row2', 'row3', 'row4']) | Creates Series my_series # Display Series my_series.shape # Show shape as tuple my_series.ndim # Dimensions as int my_series.size # Number of elements my_series.index # Show index my_seriex.values # Show values x = banana...

L5: Matplotlib and Seaborn Part 1 Bar Charts \ Imports import numpy as np import pandas as pd import matplotlib.pyplot as plt import seaborn as sb %matplotlib inline \ Read in CSV file df = pd.read_csv('pokemon.csv') print(df.shape) pokemon.head(10) \ Draw bar chart sb.countplot(data = df, x = 'cat_var'); \ Change bar color to blue base_color = sb.color_palette()[0] sb.countplot(data = df, x = 'cat_var', color = base_color) \ Change bar order (nominal-type data) cat_order = df['cat_var'...