You are viewing an old version of this page. View the current version.

Compare with Current View Page History

« Previous Version 6 Next »



Pandas DataFrames

dict = {"country": ["Brazil", "Russia", "India", "China", "South Africa"],
       "capital": ["Brasilia", "Moscow", "New Dehli", "Beijing", "Pretoria"],
       "area": [8.516, 17.10, 3.286, 9.597, 1.221],
       "population": [200.4, 143.5, 1252, 1357, 52.98] }

import pandas as pd
brics = pd.DataFrame(dict)
print(brics)


Adding index to DataFrame

# Set the index for brics
brics.index = ["BR", "RU", "IN", "CH", "SA"]

# Print out brics with new index values
print(brics)


Reading CSV by Pandas DataFrame

# Import pandas as pd
import pandas as pd

# Import the cars.csv data: cars
cars = pd.read_csv('cars.csv')

# Print out cars
print(cars)


Reading CSV file by Pandas DataFrame with 1st column as index

# Import pandas and cars.csv
import pandas as pd
cars = pd.read_csv('cars.csv', index_col = 0)

# Print out country column as Pandas Series
print(cars['cars_per_cap'])

# Print out country column as Pandas DataFrame
print(cars[['cars_per_cap']])

# Print out DataFrame with country and drives_right columns
print(cars[['cars_per_cap', 'country']])


Print partial rows (observations) from a DataFrame

# Import cars data
import pandas as pd
cars = pd.read_csv('cars.csv', index_col = 0)

# Print out first 4 observations
print(cars[0:4])

# Print out fifth, sixth, and seventh observation
print(cars[4:6])


Data access by loc and iloc in Pandas DaraFrame

loc is label-based, and iloc is integer index based

# Import cars data
import pandas as pd
cars = pd.read_csv('cars.csv', index_col = 0)

# Print out observation for Japan
print(cars.iloc[2])

# Print out observations for Australia and Egypt
print(cars.loc[['AUS', 'EG']])

Random number generation

import random

def lottery():
    # returns 6 numbers between 1 and 40
    for i in range(6):
        yield random.randint(1, 40)

    # returns a 7th number between 1 and 15
    yield random.randint(1,15)

for random_number in lottery():
       print("And the next number is... %d!" %(random_number))

Swap variables' value

a = 1
b = 2
a, b = b, a
print(a,b)

Fibonacci series generator

The first two numbers of the series is always equal to 1, and each consecutive number returned is the sum of the last two numbers - the below code uses only two variables to get the result.

def fib():
    a, b = 1, 1
    while 1:
        yield a
        a, b = b, a + b

# testing code
import types
if type(fib()) == types.GeneratorType:
    print("Good, The fib function is a generator.")

    counter = 0
    for n in fib():
        print(n)
        counter += 1
        if counter == 10:
            break

Split string as list

sentence = "the quick brown fox jumps over the lazy dog"
words = sentence.split()
print(words)

Filter positive numbers only - 1

numbers = [34.6, -203.4, 44.9, 68.3, -12.2, 44.6, 12.7]
newlist = []
for number in numbers:
    if number>0:
        newlist.append(number)
print(newlist)

Filter positive numbers only - 2

numbers = [34.6, -203.4, 44.9, 68.3, -12.2, 44.6, 12.7]
newlist = [int(x) for x in numbers if x > 0]
print(newlist)

Multiple Function Argument recognition - the list of "therest" parameters

def foo(first, second, third, *therest):
    print("First: %s" %(first))
    print("Second: %s" %(second))
    print("Third: %s" %(third))
    print("And all the rest... %s" %(list(therest)))

foo(1,2,3,4,5)

Multiple Function Argument by keyword

def bar(first, second, third, **options):
    if options.get("action") == "sum":
        print("The sum is: %d" %(first + second + third))

    if options.get("number") == "first":
        return first

result = bar(1, 2, 3, action = "sum", number = "first")
print("Result: %d" %(result))
  • No labels