rwchakra

integers = [-1, -2, -5, 0, 1, 6, 7]
naturals = []
for i in integers:
  if i >= 0:
  naturals.append(i)
  
print naturals

rwchakra

naturals = []
naturals = [i for i in integers if i >= 0]

print naturals

rwchakra

sun_data = [
[43.8, 60.5, 190.2, 144.7, 240.9, 210.3, 219.7, 176.3, 199.1, 109.2, 78.7, 67.0],
[49.9, 54.3, 109.7, 102.0, 134.5, 211.2, 174.1, 207.5, 108.2, 113.5, 68.7, 23.3],
[63.7, 72.0, 142.3, 93.5, 150.1, 158.7, 127.9, 135.5, 92.3, 102.5, 62.4, 38.5],
[51.0, 57.9, 133.4, 110.9, 112.4, 199.3, 124.0, 178.3, 102.1, 100.7, 55.7, 58.0],
[69.5, 94.3, 187.6, 152.5, 170.2, 226.9, 237.6, 242.7, 177.3, 101.3, 53.9, 59.0],
[65.9, 96.6, 122.5, 124.9, 216.3, 192.7, 269.3, 184.9, 149.1, 81.5, 48.7, 31.3],
[48.1, 62.0, 121.5, 127.3, 188.5, 196.3, 274.3, 199.9, 144.7, 102.6, 65.4, 48.9],
[43.4, 89.2, 71.4, 133.2, 179.5, 166.2, 119.2, 184.7, 79.3, 103.1, 48.9, 62.3],
[50.9, 66.6, 99.7, 103.1, 185.0, 181.3, 140.1, 202.3, 143.0, 79.1, 65.9, 41.2],

rwchakra

marks = {'Math' : 90, 'English' : 85, 'Physics' : 91, 'Chemistry' : 90, 'Economics' : 95}

print marks.keys() 
'''
Math
English
Physics
Chemistry
Economics
'''

rwchakra

marks = {'Math' : 90, 'English' : 85, 'Physics' : 91, 'Chemistry' : 90, 'Economics' : 95}

print marks['Economics'] #-> 95

print 'French' in marks #-> False

rwchakra

marks = {'Math' : 90, 'English' : 85, 'Physics' : 91, 'Chemistry' : 90, 'Economics' : 95}

# Method 1:

for subject in marks.keys():
  print subject, marks[subject]
 
'''
Economics 95
Chemistry 90

rwchakra

# -*- coding: utf-8 -*-

sentence = "There will be a full moon tonight. It’s going to be beautiful!"
vowel_count = {}

vowels = ['a', 'e', 'i', 'o', 'u']

for char in sentence:
    if char in vowels:
        vowel_count[char] = vowel_count.get(char, 0) + 1

rwchakra

subjects = ['English', 'Physics', 'Math', 'Chemistry', 'Economics']
grades = [85, 91, 90, 90, 95]
marks = {}

performance = zip(subjects, grades)

print performance #-> [('English', 85), ('Physics', 91), ('Math', 90), ('Chemistry', 90), ('Economics', 95)]

marks = dict(performance)

rwchakra

import os
import random
import re
from PIL import Image

DATA_PATH = '/path/to/your/data_dir'
FRAME_PATH = DATA_PATH+'/frames'
MASK_PATH = DATA_PATH+'/masks'

rwchakra

from keras.preprocessing.image import ImageDataGenerator

train_datagen = ImageDataGenerator(
        rescale=1./255,
        shear_range=0.2,
        zoom_range=0.2,
        horizontal_flip=True)
        
val_datagen = ImageDataGenerator(rescale=1./255)