Strings and character data in python

Python NumPy

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Random Intro
Data Distribution
Random Permutation
Seaborn Module
Normal Distribution
Binomial Distribution
Poisson Distribution
Uniform Distribution
Logistic Distribution
Multinomial Distribution
Exponential Distribution
Chi Square Distribution
Rayleigh Distribution
Pareto Distribution
Zipf Distribution

NumPy ufunc
ufunc Intro
ufunc Create Function
ufunc Simple Arithmetic
ufunc Rounding Decimals
ufunc Logs
ufunc Summations
ufunc Products
ufunc Differences
ufunc Finding LCM
ufunc Finding GCD
ufunc Trigonometric
ufunc Hyperbolic
ufunc Set Operations

Python NumPy

NumPy IntroNumPy Getting StartedNumPy Creating ArraysNumPy Array IndexingNumPy Array SlicingNumPy Data TypesNumPy Copy vs ViewNumPy Array ShapeNumPy Array ReshapeNumPy Array IteratingNumPy Array JoinNumPy Array SplitNumPy Array SearchNumPy Array SortNumPy Array FilterNumPy Random
Random Intro
Data Distribution
Random Permutation
Seaborn Module
Normal Distribution
Binomial Distribution
Poisson Distribution
Uniform Distribution
Logistic Distribution
Multinomial Distribution
Exponential Distribution
Chi Square Distribution
Rayleigh Distribution
Pareto Distribution
Zipf Distribution

NumPy ufunc
ufunc Intro
ufunc Create Function
ufunc Simple Arithmetic
ufunc Rounding Decimals
ufunc Logs
ufunc Summations
ufunc Products
ufunc Differences
ufunc Finding LCM
ufunc Finding GCD
ufunc Trigonometric
ufunc Hyperbolic
ufunc Set Operations

Escape Characters

Following table is a list of escape or non-printable characters that can be represented with backslash notation.

An escape character gets interpreted; in a single quoted as well as double quoted strings.

Backslash notation Hexadecimal character Description
\a 0x07 Bell or alert
\b 0x08 Backspace
\cx   Control-x
\C-x   Control-x
\e 0x1b Escape
\f 0x0c Formfeed
\M-\C-x   Meta-Control-x
\n 0x0a Newline
\nnn   Octal notation, where n is in the range 0.7
\r 0x0d Carriage return
\s 0x20 Space
\t 0x09 Tab
\v 0x0b Vertical tab
\x   Character x
\xnn   Hexadecimal notation, where n is in the range 0.9, a.f, or A.F

Python NumPy

NumPy IntroNumPy Getting StartedNumPy Creating ArraysNumPy Array IndexingNumPy Array SlicingNumPy Data TypesNumPy Copy vs ViewNumPy Array ShapeNumPy Array ReshapeNumPy Array IteratingNumPy Array JoinNumPy Array SplitNumPy Array SearchNumPy Array SortNumPy Array FilterNumPy Random
Random Intro
Data Distribution
Random Permutation
Seaborn Module
Normal Distribution
Binomial Distribution
Poisson Distribution
Uniform Distribution
Logistic Distribution
Multinomial Distribution
Exponential Distribution
Chi Square Distribution
Rayleigh Distribution
Pareto Distribution
Zipf Distribution

NumPy ufunc
ufunc Intro
ufunc Create Function
ufunc Simple Arithmetic
ufunc Rounding Decimals
ufunc Logs
ufunc Summations
ufunc Products
ufunc Differences
ufunc Finding LCM
ufunc Finding GCD
ufunc Trigonometric
ufunc Hyperbolic
ufunc Set Operations

Python NumPy

NumPy IntroNumPy Getting StartedNumPy Creating ArraysNumPy Array IndexingNumPy Array SlicingNumPy Data TypesNumPy Copy vs ViewNumPy Array ShapeNumPy Array ReshapeNumPy Array IteratingNumPy Array JoinNumPy Array SplitNumPy Array SearchNumPy Array SortNumPy Array FilterNumPy Random
Random Intro
Data Distribution
Random Permutation
Seaborn Module
Normal Distribution
Binomial Distribution
Poisson Distribution
Uniform Distribution
Logistic Distribution
Multinomial Distribution
Exponential Distribution
Chi Square Distribution
Rayleigh Distribution
Pareto Distribution
Zipf Distribution

NumPy ufunc
ufunc Intro
ufunc Create Function
ufunc Simple Arithmetic
ufunc Rounding Decimals
ufunc Logs
ufunc Summations
ufunc Products
ufunc Differences
ufunc Finding LCM
ufunc Finding GCD
ufunc Trigonometric
ufunc Hyperbolic
ufunc Set Operations

Join Two Sets

There are several ways to join two or more sets in Python.

You can use the method that returns a new set containing all items from both sets,
or the method that inserts all the items from one set into another:

Example

The method returns a new set with all items from both sets:

set1 = {«a», «b» , «c»}set2 = {1, 2, 3}
set3 = set1.union(set2)print(set3)

Example

The method inserts the items in set2 into set1:

set1 = {«a», «b» , «c»}set2 = {1, 2, 3}
set1.update(set2)print(set1)

Note: Both and
will exclude any duplicate items.

There are other methods that joins two sets and keeps ONLY the duplicates, or NEVER the duplicates,
check all the built-in set methods in Python.

Python Sets Tutorial
Set
Access Set Items
Add Set Items
Loop Set Items
Check if Set Item Exists
Set Length
Remove Set Items

Python NumPy

NumPy IntroNumPy Getting StartedNumPy Creating ArraysNumPy Array IndexingNumPy Array SlicingNumPy Data TypesNumPy Copy vs ViewNumPy Array ShapeNumPy Array ReshapeNumPy Array IteratingNumPy Array JoinNumPy Array SplitNumPy Array SearchNumPy Array SortNumPy Array FilterNumPy Random
Random Intro
Data Distribution
Random Permutation
Seaborn Module
Normal Distribution
Binomial Distribution
Poisson Distribution
Uniform Distribution
Logistic Distribution
Multinomial Distribution
Exponential Distribution
Chi Square Distribution
Rayleigh Distribution
Pareto Distribution
Zipf Distribution

NumPy ufunc
ufunc Intro
ufunc Create Function
ufunc Simple Arithmetic
ufunc Rounding Decimals
ufunc Logs
ufunc Summations
ufunc Products
ufunc Differences
ufunc Finding LCM
ufunc Finding GCD
ufunc Trigonometric
ufunc Hyperbolic
ufunc Set Operations

Splitting NumPy Arrays

Splitting is reverse operation of Joining.

Joining merges multiple arrays into one and Splitting breaks one
array into multiple.

We use for splitting arrays, we pass it the array we want to split
and the number of splits.

Example

Split the array in 3 parts:

import numpy as nparr = np.array()
newarr =
np.array_split(arr, 3)print(newarr)

Note: The return value is an array containing three arrays.

If the array has less elements than required, it will adjust from the end accordingly.

Example

Split the array in 4 parts:

import numpy as nparr = np.array()
newarr =
np.array_split(arr, 4)print(newarr)

Note: We also have the method available but it will not adjust the elements when elements are less in
source array for splitting like in example above, worked properly but
would fail.

Python NumPy

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Random Intro
Data Distribution
Random Permutation
Seaborn Module
Normal Distribution
Binomial Distribution
Poisson Distribution
Uniform Distribution
Logistic Distribution
Multinomial Distribution
Exponential Distribution
Chi Square Distribution
Rayleigh Distribution
Pareto Distribution
Zipf Distribution

NumPy ufunc
ufunc Intro
ufunc Create Function
ufunc Simple Arithmetic
ufunc Rounding Decimals
ufunc Logs
ufunc Summations
ufunc Products
ufunc Differences
ufunc Finding LCM
ufunc Finding GCD
ufunc Trigonometric
ufunc Hyperbolic
ufunc Set Operations

Join Two Lists

There are several ways to join, or concatenate, two or more lists in Python.

One of the easiest ways are by using the
operator.

Example

Join two list:

list1 = list2 = list3 = list1 + list2
print(list3)

Another way to join two lists are by appending all the items from list2 into
list1, one by one:

Example

Append list2 into list1:

list1 = list2 = for x in list2:  list1.append(x)print(list1)

Or you can use the
method,
which purpose is to add elements from one list to another
list:

Example

Use the method to add list2 at the end of list1:

list1 = list2 = list1.extend(list2)
print(list1)

Python Lists Tutorial
Lists
Access List Items
Change List Item
Loop List Items
Check If List Item Exists
List Length
Add List Items
Remove List Items
Copy a List

Python NumPy

NumPy IntroNumPy Getting StartedNumPy Creating ArraysNumPy Array IndexingNumPy Array SlicingNumPy Data TypesNumPy Copy vs ViewNumPy Array ShapeNumPy Array ReshapeNumPy Array IteratingNumPy Array JoinNumPy Array SplitNumPy Array SearchNumPy Array SortNumPy Array FilterNumPy Random
Random Intro
Data Distribution
Random Permutation
Seaborn Module
Normal Distribution
Binomial Distribution
Poisson Distribution
Uniform Distribution
Logistic Distribution
Multinomial Distribution
Exponential Distribution
Chi Square Distribution
Rayleigh Distribution
Pareto Distribution
Zipf Distribution

NumPy ufunc
ufunc Intro
ufunc Create Function
ufunc Simple Arithmetic
ufunc Rounding Decimals
ufunc Logs
ufunc Summations
ufunc Products
ufunc Differences
ufunc Finding LCM
ufunc Finding GCD
ufunc Trigonometric
ufunc Hyperbolic
ufunc Set Operations

Python NumPy

NumPy IntroNumPy Getting StartedNumPy Creating ArraysNumPy Array IndexingNumPy Array SlicingNumPy Data TypesNumPy Copy vs ViewNumPy Array ShapeNumPy Array ReshapeNumPy Array IteratingNumPy Array JoinNumPy Array SplitNumPy Array SearchNumPy Array SortNumPy Array FilterNumPy Random
Random Intro
Data Distribution
Random Permutation
Seaborn Module
Normal Distribution
Binomial Distribution
Poisson Distribution
Uniform Distribution
Logistic Distribution
Multinomial Distribution
Exponential Distribution
Chi Square Distribution
Rayleigh Distribution
Pareto Distribution
Zipf Distribution

NumPy ufunc
ufunc Intro
ufunc Create Function
ufunc Simple Arithmetic
ufunc Rounding Decimals
ufunc Logs
ufunc Summations
ufunc Products
ufunc Differences
ufunc Finding LCM
ufunc Finding GCD
ufunc Trigonometric
ufunc Hyperbolic
ufunc Set Operations

Splitting 2-D Arrays

Use the same syntax when splitting 2-D arrays.

Use the method, pass in the array
you want to split
and the number of splits you want to do.

Example

Split the 2-D array into three 2-D arrays.

import numpy as nparr = np.array(, , , , , ])newarr = np.array_split(arr, 3)print(newarr)

The example above returns three 2-D arrays.

Let’s look at another example, this time each element in the 2-D arrays
contains 3 elements.

Example

Split the 2-D array into three 2-D arrays.

import numpy as nparr = np.array(, , , , , ])newarr = np.array_split(arr, 3)print(newarr)

The example above returns three 2-D arrays.

In addition, you can specify which axis you want to do the split around.

The example below also returns three 2-D arrays, but they are split along the
row (axis=1).

Example

Split the 2-D array into three 2-D arrays along rows.

import numpy as nparr = np.array(, , , , , ])newarr = np.array_split(arr, 3, axis=1)
print(newarr)

An alternate solution is using opposite of

Example

Use the method to split the 2-D array into three 2-D arrays along rows.

import numpy as nparr = np.array(, , ,
, , ])newarr = np.hsplit(arr, 3)print(newarr)

Note: Similar alternates to and
are available as
and
.

Python NumPy

NumPy IntroNumPy Getting StartedNumPy Creating ArraysNumPy Array IndexingNumPy Array SlicingNumPy Data TypesNumPy Copy vs ViewNumPy Array ShapeNumPy Array ReshapeNumPy Array IteratingNumPy Array JoinNumPy Array SplitNumPy Array SearchNumPy Array SortNumPy Array FilterNumPy Random
Random Intro
Data Distribution
Random Permutation
Seaborn Module
Normal Distribution
Binomial Distribution
Poisson Distribution
Uniform Distribution
Logistic Distribution
Multinomial Distribution
Exponential Distribution
Chi Square Distribution
Rayleigh Distribution
Pareto Distribution
Zipf Distribution

NumPy ufunc
ufunc Intro
ufunc Create Function
ufunc Simple Arithmetic
ufunc Rounding Decimals
ufunc Logs
ufunc Summations
ufunc Products
ufunc Differences
ufunc Finding LCM
ufunc Finding GCD
ufunc Trigonometric
ufunc Hyperbolic
ufunc Set Operations

Python NumPy

NumPy IntroNumPy Getting StartedNumPy Creating ArraysNumPy Array IndexingNumPy Array SlicingNumPy Data TypesNumPy Copy vs ViewNumPy Array ShapeNumPy Array ReshapeNumPy Array IteratingNumPy Array JoinNumPy Array SplitNumPy Array SearchNumPy Array SortNumPy Array FilterNumPy Random
Random Intro
Data Distribution
Random Permutation
Seaborn Module
Normal Distribution
Binomial Distribution
Poisson Distribution
Uniform Distribution
Logistic Distribution
Multinomial Distribution
Exponential Distribution
Chi Square Distribution
Rayleigh Distribution
Pareto Distribution
Zipf Distribution

NumPy ufunc
ufunc Intro
ufunc Create Function
ufunc Simple Arithmetic
ufunc Rounding Decimals
ufunc Logs
ufunc Summations
ufunc Products
ufunc Differences
ufunc Finding LCM
ufunc Finding GCD
ufunc Trigonometric
ufunc Hyperbolic
ufunc Set Operations

Python NumPy

NumPy IntroNumPy Getting StartedNumPy Creating ArraysNumPy Array IndexingNumPy Array SlicingNumPy Data TypesNumPy Copy vs ViewNumPy Array ShapeNumPy Array ReshapeNumPy Array IteratingNumPy Array JoinNumPy Array SplitNumPy Array SearchNumPy Array SortNumPy Array FilterNumPy Random
Random Intro
Data Distribution
Random Permutation
Seaborn Module
Normal Distribution
Binomial Distribution
Poisson Distribution
Uniform Distribution
Logistic Distribution
Multinomial Distribution
Exponential Distribution
Chi Square Distribution
Rayleigh Distribution
Pareto Distribution
Zipf Distribution

NumPy ufunc
ufunc Intro
ufunc Create Function
ufunc Simple Arithmetic
ufunc Rounding Decimals
ufunc Logs
ufunc Summations
ufunc Products
ufunc Differences
ufunc Finding LCM
ufunc Finding GCD
ufunc Trigonometric
ufunc Hyperbolic
ufunc Set Operations

Python NumPy

NumPy IntroNumPy Getting StartedNumPy Creating ArraysNumPy Array IndexingNumPy Array SlicingNumPy Data TypesNumPy Copy vs ViewNumPy Array ShapeNumPy Array ReshapeNumPy Array IteratingNumPy Array JoinNumPy Array SplitNumPy Array SearchNumPy Array SortNumPy Array FilterNumPy Random
Random Intro
Data Distribution
Random Permutation
Seaborn Module
Normal Distribution
Binomial Distribution
Poisson Distribution
Uniform Distribution
Logistic Distribution
Multinomial Distribution
Exponential Distribution
Chi Square Distribution
Rayleigh Distribution
Pareto Distribution
Zipf Distribution

NumPy ufunc
ufunc Intro
ufunc Create Function
ufunc Simple Arithmetic
ufunc Rounding Decimals
ufunc Logs
ufunc Summations
ufunc Products
ufunc Differences
ufunc Finding LCM
ufunc Finding GCD
ufunc Trigonometric
ufunc Hyperbolic
ufunc Set Operations

Python NumPy

NumPy IntroNumPy Getting StartedNumPy Creating ArraysNumPy Array IndexingNumPy Array SlicingNumPy Data TypesNumPy Copy vs ViewNumPy Array ShapeNumPy Array ReshapeNumPy Array IteratingNumPy Array JoinNumPy Array SplitNumPy Array SearchNumPy Array SortNumPy Array FilterNumPy Random
Random Intro
Data Distribution
Random Permutation
Seaborn Module
Normal Distribution
Binomial Distribution
Poisson Distribution
Uniform Distribution
Logistic Distribution
Multinomial Distribution
Exponential Distribution
Chi Square Distribution
Rayleigh Distribution
Pareto Distribution
Zipf Distribution

NumPy ufunc
ufunc Intro
ufunc Create Function
ufunc Simple Arithmetic
ufunc Rounding Decimals
ufunc Logs
ufunc Summations
ufunc Products
ufunc Differences
ufunc Finding LCM
ufunc Finding GCD
ufunc Trigonometric
ufunc Hyperbolic
ufunc Set Operations

String Methods

Python has a set of built-in methods that you can use on strings.

Note: All string methods returns new values. They do not change the original string.

Method Description
capitalize() Converts the first
character to upper case
casefold() Converts string into
lower case
center() Returns a centered
string
count() Returns the number of
times a specified value occurs in a string
encode() Returns an encoded
version of the string
endswith() Returns true if the
string ends with the specified value
expandtabs() Sets the
tab size of the string
find() Searches the string for a
specified value and returns the position of where it was found
format() Formats specified
values in a string
format_map() Formats specified
values in a string
index() Searches the string
for a specified value and returns the position of where it was found
isalnum() Returns True if all
characters in the string are alphanumeric
isalpha() Returns True if all
characters in the string are in the alphabet
isdecimal() Returns True if all
characters in the string are decimals
isdigit() Returns True if all
characters in the string are digits
isidentifier() Returns True if
the string is an identifier
islower() Returns True if all
characters in the string are lower case
isnumeric() Returns True if
all characters in the string are numeric
isprintable() Returns True if
all characters in the string are printable
isspace() Returns True if all
characters in the string are whitespaces
istitle() Returns True if the string follows the rules of a
title
isupper() Returns True if all
characters in the string are upper case
join() Joins the elements of
an iterable to the end of the string
ljust() Returns a left justified
version of the string
lower() Converts a string into
lower case
lstrip() Returns a left trim
version of the string
maketrans() Returns a
translation table to be used in translations
partition() Returns a tuple
where the string is parted into three parts
replace() Returns a string
where a specified value is replaced with a specified value
rfind() Searches the string for
a specified value and returns the last position of where it was found
rindex() Searches the string for
a specified value and returns the last position of where it was found
rjust() Returns a right justified
version of the string
rpartition() Returns a tuple
where the string is parted into three parts
rsplit() Splits the string at
the specified separator, and returns a list
rstrip() Returns a right trim
version of the string
split() Splits the string at
the specified separator, and returns a list
splitlines() Splits the string
at line breaks and returns a list
startswith() Returns true if
the string starts with the specified value
strip() Returns a trimmed version of the string
swapcase() Swaps cases, lower
case becomes upper case and vice versa
title() Converts the first
character of each word to upper case
translate() Returns a
translated string
upper() Converts a string
into upper case
zfill() Fills the string with
a specified number of 0 values at the beginning

Python NumPy

NumPy IntroNumPy Getting StartedNumPy Creating ArraysNumPy Array IndexingNumPy Array SlicingNumPy Data TypesNumPy Copy vs ViewNumPy Array ShapeNumPy Array ReshapeNumPy Array IteratingNumPy Array JoinNumPy Array SplitNumPy Array SearchNumPy Array SortNumPy Array FilterNumPy Random
Random Intro
Data Distribution
Random Permutation
Seaborn Module
Normal Distribution
Binomial Distribution
Poisson Distribution
Uniform Distribution
Logistic Distribution
Multinomial Distribution
Exponential Distribution
Chi Square Distribution
Rayleigh Distribution
Pareto Distribution
Zipf Distribution

NumPy ufunc
ufunc Intro
ufunc Create Function
ufunc Simple Arithmetic
ufunc Rounding Decimals
ufunc Logs
ufunc Summations
ufunc Products
ufunc Differences
ufunc Finding LCM
ufunc Finding GCD
ufunc Trigonometric
ufunc Hyperbolic
ufunc Set Operations

Python NumPy

NumPy IntroNumPy Getting StartedNumPy Creating ArraysNumPy Array IndexingNumPy Array SlicingNumPy Data TypesNumPy Copy vs ViewNumPy Array ShapeNumPy Array ReshapeNumPy Array IteratingNumPy Array JoinNumPy Array SplitNumPy Array SearchNumPy Array SortNumPy Array FilterNumPy Random
Random Intro
Data Distribution
Random Permutation
Seaborn Module
Normal Distribution
Binomial Distribution
Poisson Distribution
Uniform Distribution
Logistic Distribution
Multinomial Distribution
Exponential Distribution
Chi Square Distribution
Rayleigh Distribution
Pareto Distribution
Zipf Distribution

NumPy ufunc
ufunc Intro
ufunc Create Function
ufunc Simple Arithmetic
ufunc Rounding Decimals
ufunc Logs
ufunc Summations
ufunc Products
ufunc Differences
ufunc Finding LCM
ufunc Finding GCD
ufunc Trigonometric
ufunc Hyperbolic
ufunc Set Operations

Escape Character

To insert characters that are illegal in a string, use an escape character.

An escape character is a backslash followed by the character you want to insert.

An example of an illegal character is a double quote inside a string that is surrounded by double quotes:

Example

You will get an error if you use double quotes inside a string that is
surrounded by double quotes:

txt = «We are the so-called «Vikings» from the north.»

To fix this problem, use the escape character :

Example

The escape character allows you to use double quotes when you normally would not be allowed:

txt = «We are the so-called \»Vikings\» from the north.»

Other escape characters used in Python:

Code Result Try it
\’ Single Quote Try it »
\\ Backslash Try it »
\n New Line Try it »
\r Carriage Return Try it »
\t Tab Try it »
\b Backspace Try it »
\f Form Feed
\ooo Octal value Try it »
\xhh Hex value Try it »

Python NumPy

NumPy IntroNumPy Getting StartedNumPy Creating ArraysNumPy Array IndexingNumPy Array SlicingNumPy Data TypesNumPy Copy vs ViewNumPy Array ShapeNumPy Array ReshapeNumPy Array IteratingNumPy Array JoinNumPy Array SplitNumPy Array SearchNumPy Array SortNumPy Array FilterNumPy Random
Random Intro
Data Distribution
Random Permutation
Seaborn Module
Normal Distribution
Binomial Distribution
Poisson Distribution
Uniform Distribution
Logistic Distribution
Multinomial Distribution
Exponential Distribution
Chi Square Distribution
Rayleigh Distribution
Pareto Distribution
Zipf Distribution

NumPy ufunc
ufunc Intro
ufunc Create Function
ufunc Simple Arithmetic
ufunc Rounding Decimals
ufunc Logs
ufunc Summations
ufunc Products
ufunc Differences
ufunc Finding LCM
ufunc Finding GCD
ufunc Trigonometric
ufunc Hyperbolic
ufunc Set Operations

Join Two or More Tables

You can combine rows from two or more tables, based on a related column
between them, by using a JOIN statement.

Consider you have a «users» table and a «products» table:

users

{ id: 1, name: ‘John’, fav: 154},{ id:
2, name: ‘Peter’, fav: 154},{ id: 3, name: ‘Amy’, fav: 155},{ id: 4, name: ‘Hannah’, fav:},{ id: 5, name: ‘Michael’, fav:}

products

{ id: 154, name:
‘Chocolate Heaven’ },{ id: 155, name: ‘Tasty Lemons’ },{
id: 156, name: ‘Vanilla Dreams’ }

These two tables can be combined by using users’ field and products’
field.

Example

Join users and products to see the name of the users favorite product:

import mysql.connectormydb = mysql.connector.connect(  host=»localhost», 
user=»yourusername»,  password=»yourpassword»,  database=»mydatabase»)
mycursor = mydb.cursor()sql = «SELECT \  users.name AS user,
\  products.name AS favorite \  FROM users \  INNER JOIN
products ON users.fav = products.id»mycursor.execute(sql)
myresult = mycursor.fetchall()for x in myresult:  print(x)

Note: You can use JOIN instead of INNER JOIN. They will
both give you the same result.

Python NumPy

NumPy IntroNumPy Getting StartedNumPy Creating ArraysNumPy Array IndexingNumPy Array SlicingNumPy Data TypesNumPy Copy vs ViewNumPy Array ShapeNumPy Array ReshapeNumPy Array IteratingNumPy Array JoinNumPy Array SplitNumPy Array SearchNumPy Array SortNumPy Array FilterNumPy Random
Random Intro
Data Distribution
Random Permutation
Seaborn Module
Normal Distribution
Binomial Distribution
Poisson Distribution
Uniform Distribution
Logistic Distribution
Multinomial Distribution
Exponential Distribution
Chi Square Distribution
Rayleigh Distribution
Pareto Distribution
Zipf Distribution

NumPy ufunc
ufunc Intro
ufunc Create Function
ufunc Simple Arithmetic
ufunc Rounding Decimals
ufunc Logs
ufunc Summations
ufunc Products
ufunc Differences
ufunc Finding LCM
ufunc Finding GCD
ufunc Trigonometric
ufunc Hyperbolic
ufunc Set Operations

Built-in String Methods

Python includes the following built-in methods to manipulate strings −

Sr.No. Methods with Description
1 capitalize()

Capitalizes first letter of string

2 center(width, fillchar)

Returns a space-padded string with the original string centered to a total of width columns.

3 count(str, beg= 0,end=len(string))

Counts how many times str occurs in string or in a substring of string if starting index beg and ending index end are given.

4 decode(encoding=’UTF-8′,errors=’strict’)

Decodes the string using the codec registered for encoding. encoding defaults to the default string encoding.

5 encode(encoding=’UTF-8′,errors=’strict’)

Returns encoded string version of string; on error, default is to raise a ValueError unless errors is given with ‘ignore’ or ‘replace’.

6 endswith(suffix, beg=0, end=len(string))

Determines if string or a substring of string (if starting index beg and ending index end are given) ends with suffix; returns true if so and false otherwise.

7 expandtabs(tabsize=8)

Expands tabs in string to multiple spaces; defaults to 8 spaces per tab if tabsize not provided.

8 find(str, beg=0 end=len(string))

Determine if str occurs in string or in a substring of string if starting index beg and ending index end are given returns index if found and -1 otherwise.

9 index(str, beg=0, end=len(string))

Same as find(), but raises an exception if str not found.

10 isalnum()

Returns true if string has at least 1 character and all characters are alphanumeric and false otherwise.

11 isalpha()

Returns true if string has at least 1 character and all characters are alphabetic and false otherwise.

12 isdigit()

Returns true if string contains only digits and false otherwise.

13 islower()

Returns true if string has at least 1 cased character and all cased characters are in lowercase and false otherwise.

14 isnumeric()

Returns true if a unicode string contains only numeric characters and false otherwise.

15 isspace()

Returns true if string contains only whitespace characters and false otherwise.

16 istitle()

Returns true if string is properly «titlecased» and false otherwise.

17 isupper()

Returns true if string has at least one cased character and all cased characters are in uppercase and false otherwise.

18 join(seq)

Merges (concatenates) the string representations of elements in sequence seq into a string, with separator string.

19 len(string)

Returns the length of the string

20 ljust(width)

Returns a space-padded string with the original string left-justified to a total of width columns.

21 lower()

Converts all uppercase letters in string to lowercase.

22 lstrip()

Removes all leading whitespace in string.

23 maketrans()

Returns a translation table to be used in translate function.

24 max(str)

Returns the max alphabetical character from the string str.

25 min(str)

Returns the min alphabetical character from the string str.

26 replace(old, new )

Replaces all occurrences of old in string with new or at most max occurrences if max given.

27 rfind(str, beg=0,end=len(string))

Same as find(), but search backwards in string.

28 rindex( str, beg=0, end=len(string))

Same as index(), but search backwards in string.

29 rjust(width,)

Returns a space-padded string with the original string right-justified to a total of width columns.

30 rstrip()

Removes all trailing whitespace of string.

31 split(str=»», num=string.count(str))

Splits string according to delimiter str (space if not provided) and returns list of substrings; split into at most num substrings if given.

32 splitlines( num=string.count(‘\n’))

Splits string at all (or num) NEWLINEs and returns a list of each line with NEWLINEs removed.

33 startswith(str, beg=0,end=len(string))

Determines if string or a substring of string (if starting index beg and ending index end are given) starts with substring str; returns true if so and false otherwise.

34 strip()

Performs both lstrip() and rstrip() on string.

35 swapcase()

Inverts case for all letters in string.

36 title()

Returns «titlecased» version of string, that is, all words begin with uppercase and the rest are lowercase.

37 translate(table, deletechars=»»)

Translates string according to translation table str(256 chars), removing those in the del string.

38 upper()

Converts lowercase letters in string to uppercase.

39 zfill (width)

Returns original string leftpadded with zeros to a total of width characters; intended for numbers, zfill() retains any sign given (less one zero).

40 isdecimal()

Returns true if a unicode string contains only decimal characters and false otherwise.

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Python NumPy

NumPy IntroNumPy Getting StartedNumPy Creating ArraysNumPy Array IndexingNumPy Array SlicingNumPy Data TypesNumPy Copy vs ViewNumPy Array ShapeNumPy Array ReshapeNumPy Array IteratingNumPy Array JoinNumPy Array SplitNumPy Array SearchNumPy Array SortNumPy Array FilterNumPy Random
Random Intro
Data Distribution
Random Permutation
Seaborn Module
Normal Distribution
Binomial Distribution
Poisson Distribution
Uniform Distribution
Logistic Distribution
Multinomial Distribution
Exponential Distribution
Chi Square Distribution
Rayleigh Distribution
Pareto Distribution
Zipf Distribution

NumPy ufunc
ufunc Intro
ufunc Create Function
ufunc Simple Arithmetic
ufunc Rounding Decimals
ufunc Logs
ufunc Summations
ufunc Products
ufunc Differences
ufunc Finding LCM
ufunc Finding GCD
ufunc Trigonometric
ufunc Hyperbolic
ufunc Set Operations

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