PythonBasics Flashcards

Question

find files

Answer 1

use mv (move a file) so you write “mv filename.doc newfilename.doc”. you can check the name change after by listing the directory content with ls

Answer 2

write “less filename.txt” and it will show you the content. To quit, just type q

Answer 3

just write “rm filename.doc” (you can also remove multiple files at once by listing them)

Answer 4

rmdir foldername

Answer 5

rm foldername/filename.txt

Answer 6

rm -rf foldername

Answer 7

sudo makes you a super-user and lets you force through more commands

Answer 8

Just write “python filename.py”

Answer 9

A hash. If you put a hash (#) in front of a line of code, it will not print / go in effect so you can use it for making comments

Answer 10

you put it inside strings; print “we have a # inside of the strings now” # the hash inside the strings will be printed but this comment after the second # will not be printed.

Answer 11

slash and it is the division sign

Answer 12

asterisk and it is the multiplier sign

Answer 13

with “+” for example “print 3 + 2” will output 5

Answer 14

with “-” for example “print 3 - 4” will output -1

Answer 15

percent and it works as ‘X divided by Y with J remaining’. For example, “100 divided by 16 with 4 remaining” so print “100 % 16” will be 4. While 100 % 10 will be 0.

Answer 16

Essentially just numbers that include decimals such as 5.5 or 0.02

Answer 17

6… if you want the precise output including decimals you need to write print “20.0/3.0) and you will get 6.666666666666667

Answer 18

PEMDAS, Parentheses, exponents, multiplication, division, addition, subtraction

Answer 19

you basically just write out with a “=” sign in-between so for example, “Cars = 100” # creates a variable that ‘cars’ is equal to 100 “cars\_not\_driven = cars – drivers” # creates a variable for available cars (cars\_not\_driven)

Answer 20

The = (single-equal) assigns the value on the right to a variable on the left. The == (double-equal) tests if two things have the same value.

Answer 21

You can, but it’s bad form. You should add space around operators like this so that it’s easier to read.

Answer 22

Examples… My\_name = “Lars Horsbol” And My\_age = 23

Answer 23

you use %s for character-variables and %d for number variables. For example, Print “Let’s talk about %s” % my\_name And Print “He’s %d centimeters tall.” % my\_age

Answer 24

With %d Print “He’s %d centimeters tall.” % my\_age

Answer 25

With %s Print “Let’s talk about %s” % my\_name

Answer 26

You just write them out in the %d. print "If I add %d, %d, and %d I get %d." % (my\_age, my\_height, my\_weight, my\_age + my\_height + my\_weight) here we are trying to add the variables together

Answer 27

If you use %r, it will print no matter what, meaning that it will both print a character-variable (normally %s) and a number-variable (normally %d). print "and with both character %r AND number %r" % (height, hair) # with %r we will end up printing both the character-variable AND the number-variable and with both character 192 AND number 'Dark-blond'

Answer 28

%d = signed integer decimal %s = character-variables %r = ”print this no matter what”

Answer 29

The %r is best for debugging, and the other formats are for actually displaying variables to users.

Answer 30

No, the 1 is not a valid variable name. They need to start with a character, so a1 would work, but 1 will not.

Answer 31

We write “% 10” x = "There are %d types of people." % 10 # here we write a string and insert a variable with % outside the string

Answer 32

just write; print w + e

Answer 33

You can use the **round()** function like this: **round(1.7333)** or round(weight / pounds\_to\_kilo)

Answer 34

In Python either way to make a string is acceptable, although typically you’ll use single-quotes for any short strings like 'a' or 'snow' and double-quotes for sentences.

Answer 35

You should use %s and only use %r for getting debugging information about something. The %r will give you the “raw programmer’s” version of variable, also known as the “representation.”

Answer 36

Mostly it’s because of style, but I’ll use a single-quote inside a string that has double-quotes. Look at line 10 to see how I’m doing that. print "I also said: '%s'." % y

Answer 37

this will result in 10\*. So the output will be; ……….

Answer 38

Just. Cheese burger On two different lines because there is no comma after “end6”.

Answer 39

That’s because Python recognizes True and False as keywords representing the concept of true and false. If you put quotes around them, then they are turned into strings and won’t work right.

Answer 40

Just. Cheese burger On two different lines because there is a comma after “end6” it stays on the same line in the printed output.

Answer 41

Its fleece was white as snow.

Answer 42

'%r %r %r %r' '%r %r %r %r' '%r %r %r %r' '%r %r %r %r'

Answer 43

'I had this thing.' 'That you could type up right.' "But it didn't sing." 'So I said goodnight.'

Answer 44

That’s because Python recognizes True and False as keywords representing the concept of true and false. If you put quotes around them, then they are turned into strings and won’t work right.

Answer 45

Use %s to print that instead and it’ll work.

Answer 46

Python is going to print the strings in the most efficient way it can, not replicate exactly the way you wrote them. This is perfectly fine since %r is used for debugging and inspection, so it’s not necessary that it be pretty.

Answer 47

That’s how %r formatting works; it prints it the way you wrote it (or close to it). It’s the “raw” format for debugging.

Answer 48

1. You can use \n è "nJan\nFeb\nMar\nApr\nMay\nJun\nJul\nAug" 2. You can use a triple double quote “”” ………… “””

Answer 49

Write a lot of text within the “”” here “”” on multiple different lines print """ There's something going on here. With the three double-quotes. We'll be able to type as much as we like. Even 4 lines if we want, or 5, or 6. """

Answer 50

You use; \t so for example Print "\tI'm tabbed in."

Answer 51

You use \n so for example… Print "I'm split\non a line." Will become; I’m split On a line

Answer 52

I’m \ a \ cat So it removes one of the backlashes

Answer 53

It inserts an extra space. So; Print “hey man\a whats up” Becomes Hey man whats up

Answer 54

That’s because %r is printing out the raw representation of what you typed, which is going to include the original escape sequences. Use %s instead. Always remember this: %r is for debugging; %s is for displaying.

Answer 55

the function of the comma is to make sure that the output is on the same line. With comma we get; How old are you? 23 Without comma we get: How old are you? 23

Answer 56

Raw\_input lets you interact with the outside world to get input. The raw\_input() function waits for the user to type some input and press return. It then gets whatever was typed. (called input() in python 3 but here it also tries to convert the input whereas rawinput from python 2 simply takes the raw input which is usually easier to work with/safer)

Answer 57

Just write questions or prompts inside the string of the raw\_input() like this; height = raw\_input("How tall are you? Fx. 1.82 m")

Answer 58

Remember, %r is for debugging and is “raw representation” while %s is for display. I will not answer this question again, so you must memorize this fact. This is the #1 thing people ask repeat- edly, and asking the same question over and over means you aren’t taking the time to memorize what you should. Stop now, and finally memorize this fact.

Answer 59

Modules are features you can add in your python script. Some people also called modules for libraries. It could for example be: sys and argv

Answer 60

Python filename.py arg1 arg2 arg3 So for example Python e13.py I want snacks Will give… The script is called: e13.py Your first variable is: i Your second variable is: want Your third variable is: snacks

Answer 61

The difference has to do with where the user is required to give input. If they give your script inputs on the command line, then you use argv. If you want them to input using the keyboard while the script is running, then use raw\_input().

Answer 62

No, it doesn’t. It actually makes something called a “file object.” You can think of it like an old tape drive that you saw on mainframe computers in the 1950s or even like a DVD player from today. You can move around inside them, and then “read” them, but the file is not the contents

Answer 63

For now, just understand that sys is a package, and this phrase just says to get the argv feature from that package. You’ll learn more about these later.

Answer 64

Python will not restrict you from opening a file more than once, and in fact sometimes this is necessary.

Answer 65

Write(stuff)

Answer 66

This is the default mode. It Opens file for reading.

Answer 67

This Mode Opens file for writing. If file does not exist, it creates a new file. If file exists it truncates the file.

Answer 68

Creates a new file. If file already exists, the operation fails.

Answer 69

Open file in append mode. If file does not exist, it creates a new file.

Answer 70

This is the default mode. It opens in text mode.

Answer 71

This opens in binary mode.

Answer 72

This will open a file for reading and writing (updating)

Answer 73

No. It doesn’t make any difference as the “w-mode” will overwrite the existing file so emptying that file first makes no difference.

Answer 74

Yes, that’s the default for the open() function.

Answer 75

With the import statement we can import new modules to python. Some modules/functions are existing in your python program already, but sometimes you may want to add new functions. Here, it can be smart to import code written by others than to innovate yourself. You can import such new modules with the import statement.

Answer 76

It is good practice to always close files so you avoid later commands working with those files from reading descriptions from those closed files.

Answer 77

It gets the length of the string that you pass to it and then returns that as a number. Play with it.

Answer 78

1. They name pieces of code the way variables name strings and numbers. 2. They take arguments the way your scripts take argv. 3. Using #1 and #2, they let you make your own “mini-scripts” or “tiny commands.” Think of “function” as a mini-script

Answer 79

Write; def (for define)

Answer 80

The first function is overly complicated. It takes the look of when we work with args and does uses \*args inside print\_two. On the line below, it unpacks those args to finally print it. There is no need to do this unpacking. We can simply put arg1, arg2 inside the function from the beginning.

Answer 81

1. With; def (for definition) 2. And then open paranteheses right after the function name 3. And list the arguments comma separated 4. End the parantehese AND add a colon: def print\_three(arg1, arg2, arg3):

Answer 82

It should only use characters AND underscore so for example Print\_two\_again

Answer 83

4 characters. No more, no less. This usually happens automatically in your script-writing program

Answer 84

The same as to “use” or to “call” a function

Answer 85

The same as to “run” or to “call” a function

Answer 86

The same as to “use” or to “use” a function

Answer 87

Just like variable names, anything that doesn’t start with a number and is letters, numbers, and underscores will work

Answer 88

That tells Python to take all the arguments to the function and then put them in args as a list. It’s like argv that you’ve been using, but for functions. It’s not normally used too often unless specifi- cally needed.

Answer 89

No. The functions you write in your script are not connected to the variables.

Answer 90

it will print: We can just give the function numbers directly: You have 20 cheeses! You have 30 boxes of crackers! Man that's enough for a party! Get a blanket. As it will first “We can just give the function numbers directly:” and then all the content of the function (def) Cheese\_and\_crackers below it.

Answer 91

Put raw\_input inside int() for integer For example Eaten\_packages = int(raw\_input(“How many packages did you eat by now? “))

Answer 92

It depends on the version of Python and the computer you’re on, but it is fairly large. The practical limit, though, is about five arguments before the function becomes annoying to use.

Answer 93

The seek-function takes the “cursor” (or point of the mouse so to say) to a certain place in a file. For example, we take it to the very beginning with f.seek(0) so we are at the start of the file again

Answer 94

`+=` adds another value with the variable's value and assigns the new value to the variable. `+=` adds a number to a variable, changing the variable itself in the process (whereas `+` would not). It adds the right operand to the left. `x += 2` means `x = x + 2`

Answer 95

`+=` subctracts a number from a variable, changing the variable itself in the process (whereas `-` would not). It subtracts the right operand from the left. `x -= 2` means `x = x - 2`

Answer 96

`*=` multiplies a number with a variable, changing the variable itself in the process (whereas `*` would not). It multiplies the right operand with the left. `x *= 2` means `x = 2x`

Answer 97

`/=` divides a variable with a number, changing the variable itself in the process (whereas `/` would not). It divides the right operand with the left. `x /= 2` means `x = x/2`

Answer 98

`%=` finds modulus of a variable with a number, changing the variable itself in the process (whereas `%` would not). Modulus = the remainder when dividing. It finds modulus so: `x %= 3` means `x = modulus of x/3`

Answer 99

Inside readline() is code that scans each byte of the file until it finds a \n character, then stops reading the file to return what it found so far. The file f is responsible for maintaining the current position in the file after each readline() call, so that it will keep reading each line.

Answer 100

The RETURN statement writes out what it does to the user AND can also be used by other functions The PRINT statement simply writes out what’s inside but cannot be used by other functions _Example explanation:_ Def returnFunction(num): Num = num \*2 Return num Def printFunction(num): Num = num \*2 Print(num) If we write… returnFunction(4) we get an output of; 8 if we write…. printFunction(4) we get an output of; 8 So as such they look the same. But.. heres the difference. X = returnFunction(4) X #notice this one 8 Y = printFunction(4) 8 So the return function gives us “x” but the print-function doesn’t give us anything so we cannot use it later. If we in python now ask for x we will get 8 but if we ask for y we won’t get anything.

Answer 101

Remember int(raw\_input())? The problem with that is then you can’t enter floating point, so also try using float(raw\_input()) instead.

Answer 102

It’s the same as “output”. Synonyms.

Answer 103

Write # and everything here after the hashtag will not be shown. It is called HASH or and OCTOTHORPE But you can still write an octothorpe inside strings like: Print “here we # like to go on Instagram”

Answer 104

Remember to put a comma… Print “Hens”, 25 + 5 Will return Hens 30 Or Print “What is 3 + 2?”, 3 +2 Will return What is 3 + 2? 5

Answer 105

Simple use = For example Cars = 100

Answer 106

If you use %r, it will print no matter what, meaning that it will both print a character-variable (normally %s) and a number-variable (normally %d). print "and with both character %r AND number %r" % (height, hair) # with %r we will end up printing both the character-variable AND the number-variable and with both character 192 AND number 'Dark-blond'

Answer 107

Just write asterisk and the number of times you want to repeat it. For example: Print “.” \* 20 Will return ………………..

Answer 108

Use \n For example: Months = 'Jan\nFeb\nMar\nApr\nMay\nJun\nJul\nAug' Print “Here are the months: “, months

Answer 109

Use \t So for example Print “”” I’ll do a list: \t\* Sugar \t\* Spice \t\* And everything nice Will return I’ll do a list * Sugar * Spice * And everything nice

Answer 110

Use raw\_input() For example… Print “How old are you?”, Age = raw\_input() remember the comma after print

Answer 111

Import argv by writing… From sys import argv

Answer 112

Yes. This is called a prompt. Help for the answer For example Print “What’s your birthday? “, Raw\_input(“DD-MM-YYYY” )

Answer 113

Write first the argument inoputs such as… Script, filename = argv #script name and filename is defined here.

Answer 114

Open(filename, “w”) #note… you must define filename.

Answer 115

Target.truncate()

Answer 116

Target.write()

Answer 117

Target.close()

Answer 118

open(from\_file, “r”) #note you must define from\_file

Answer 119

First you open command and run “python” Then you “import file1” (whatever file it is) And then tell python to run a certain function within “file1” by adding “dot” and the function’s name. For example: E25.print\_last\_word(sorted\_words)

Answer 120

This function will break up word for us.

Answer 121

Prints the first and last words of the sentence.

Answer 122

Sorts the words then prints the first and last one.

Answer 123

Prints the first word after popping it off.

Answer 124

Prints the last word after popping it off.

Answer 125

Takes in a full sentence and returns the sorted words.

Answer 126

Sorts the words.

Answer 127

lists - consist of a countable number of ordered values - fruits = [’orange ’ , ’apple ’ , ’pear ’ , ’banana ’ , ’kiwi’, ’apple’, ’banana’]

Answer 128

* Immutable: Cannot be changed * The advantage is that you will know the position of the elements better and thus also make it easier for the computer to locate elements: provides for speed * You use it when you know that a variable will not change (e.g. days of the week) * Values are separated by commas * v = (’a’, ’b’, ’c’)

Answer 129

sets * unordered collection * NO duplicate elements * basket = {’apple’, ’orange’, ’apple’, ’pear’, ’orange’, ’banana’}

Answer 130

dictionary * a set of keys: value pairs in which each key is unique * tel = {’jack’: 4098, ’john’: 4139}

Answer 131

classes are used to create new user-defined data structures that contain arbitrary information about something. Class is generic. * Class: Dog * species = ’mammal ’ an object/instance is a copy of the class with actual values (thus you have 1 class and multiple instances). Object/instance is specific. * Instance/object: * def \_\_init\_\_(self , name, age): self .name = name * self .age = age

Answer 132

* For-loops you know in advance the number of times it will execute. This is unknown with while-loops as it executes as long as the Boolean condition is True * Use a for-loop for definite iterations = if you know the maximum number of times that you need to execute the code * Use a while-loop if you require to repeat some computation until a condition is met that you cannot calculate in advance (needed for probabilistic results and human intervention)

Answer 133

a break statement is used to immediately finish a loop. (this is considered bad practice though)

Answer 134

a continue statement causes to skip the processing of the rest of the code for a loop BUT the loop continues with the subsequent iterations of the loop (this is considered bad practice though)

Answer 135

* Missing punctuation characters, such as parentheses, quotation marks or commas

Answer 136

* when you try to combine to incompatible items

Answer 137

* Normally when you have used a variable before assigning it a value

Answer 138

* When the value passed to a function is not compatible with the function. * in the example as string inserted as if it was to be converted to an integer

Answer 139

TIRTBV * Title * Introduce * Reproduce (others should be able to reproduce) * Tags * Background * Version

Answer 140

A = 2 is defining a as 2 A == 2 is asking whether a is equal to 2 or not

Answer 141

* Names can not start with a number * Use _ when using space * Do not use capital letter (best practice is lowercase)

Answer 142

* Float * Integer * Boolean

Answer 143

* Addition (i.e. +) * Substraction (i.e. -) * Multiplication (i.e. \*) * Division (i.e. /) * Power functions (i.e. \*\*) * Modulo (i.e. %)

Answer 144

The numbers have not been rounded and are only showing with one decimal. To turn to 0 write: round(0.1+0.2-0.3)

Answer 145

Count number of characters in "Hello world" my\_text = 'Hello world' len(my\_text) 11

Answer 146

O H = 0, e = 1, 2 = l, 3=l, o=4, “ “ = 5, w=6, o=7

Answer 147

len(set(my\_list)) 6 set(my\_list) {1, 2, 3, 4, 5, 9}

Answer 148

print(a ^ b) #symmetric difference is everything that is not in the intersection, everything that’s not in common {1, 4}

Answer 149

2 4 6 8 (A is the initial value, B is how far it should go and C is the steps) (2, 10, 2) will turn out as 2, 4, 6, 8 (but not 10) You can do this much more efficiently… for i in range(2, 10, 2): print(i) #this version is much more efficient as it will not spent time on #1, 3, 5, 7, 9 so we save CPU power

Answer 150

for x in range(1, 11, 1): for y in range(1, 11, 1): print((x\*y), end=" ") print()

Answer 151

list\_Numbers = [1, 2, 3, 4] l = [i\*\*2 for i in list\_Numbers if i\*\*2 \> 8] l with list comprehension you create a NEW list so you have [] around it and then here I have defined the new list containing 9, 16 as "l" you can add the new list to an existing list with .append list\_Numbers.append(l) list\_Numbers [1, 2, 3, 4, [9, 16]]

Answer 152

Now let’s talk about WHILE-LOOPS, which executes an unknown number of times, as long as the Boolean condition is True

Answer 153

with open(‘data.txt’, ‘r’) as f for line in f: print(line) this will read the file line by line #you can also do it this way…. with open(‘data.txt’, ‘r’) as f: data = f.read() however, this reads everything in one line so if there are no line shifts in the file you will get one looooooong line

Answer 154

With try and except try: run my freaking code here and except: if it does not work then try to do this thing to fix it

Answer 155

write the specified name.close()

Answer 156

You can use… endswith() startswith() fnmatch.fnmatch()

Answer 157

**NumPy** is a Python module. It stands for ’Numerical Python’. It is a library consisting of multidimensional array objects and a collection of functions to process them.

Answer 158

* An array is a data structure consisting of a collection of values, each one identified by at least one positive index (can have more than one dimension; matrixes) * all values have the same type (int, float….) * (array = objects, ndarray = class name of these objects) * each element within this is a “dtype” (data-type) element in NumPy

Answer 159

* clear variable and function names * consistency in styling; ‘ vs “ * Duplication vs. abstraction * Group like items in your code so that it is more reusable * Break long program into different files

Answer 160

* R * Focuses on better, user friendly data analysis, statistics and graphical models * Academics, researchers, data scientists * Python * Object based and emphasizes productivity and code reliability * Programmers, data scientists

Answer 161

x = [1, 2, 3] a = np.asarray(x) [1, 2, 3] or… a = np.asarray(x, dtype = float) [1. , 2. , 3.]

Answer 162

np.multiply(a,b). Multiply two arrays element wise

Answer 163

np.matmul(a,b). Performs a matrix multiplication

Answer 164

**np.amax(a).** Retrieve the largest element

Answer 165

A series is a one-dimensional labeled array and can be created using the following code

Answer 166

* **Syntax errors** occur when the parser detects an incorrect statement * **An exception** error occurs whenever syntactically correct python code results in an error

Answer 167

Assertions are a systemic way to check that the inputs in a program are as expected by the program to avoid running into exception errors. Often useful for: * checking parameter types, classes or values, * checking “can’t happen” situations such as dividing by 0 * after calling a function to make sure that its return is reasonable assert condition, error\_message

Answer 168

To implement some sort of action to clean up after executing a code.

Answer 169

df = df.drop(columns = [‘ColumnName1’, ‘ColumnName2’])

Answer 170

The function applymap() applies a function to each element of a DataFrame (two-dimensional data structure) apply() # by itself will only add to the specific column.. and apply(\_\_\_\_\_\_, axis = 1) # will add to a row

Answer 171

nan = Not a Number and is the result you get when applying functions to a DataFrame that has null values. To detect missing values in your dataframe you can use the isnull() and notnull() functions.

Answer 172

you can also rename the function at the same time… from fibo import fib\_print as fibonacci

Answer 173

it basically fails as the second list only contains two elements.

Answer 174

a[-1][-2:] returns… array ([5, 6]) why? you basically have…

Answer 175

y = np.arange(101) y[y%2==0] array([0, 2, 4, 6, 8, 10, 12 ………. 100)] note that arange only has one r.

Answer 176

this is broadcasting… we have an array with 3 elements starting from 0 and we add 5. array([5, 6, 7])

Answer 177

this is broadcasting… Here we first create np.ones((3,3)) which is 1, 1, 1 1, 1, 1 1, 1, 1 and then np.arange(3) on top of it so it is increasing by adding 0, then 1, then 2.

Answer 178

this is broadcasting… np.arange(3) is.. 0, 1, 2 BUT…. it is reshaped to 3 rows, 1 column… so… 0 1 2 and then we add another np.arange(3) to it… 0, 1, 2 and combine to… 0, 1, 2 1, 2, 3 2, 3, 4

Answer 179

say… a = np.array([1, 2, 3, 4]) for x in np.nditer(a): print (x\*x) 1, 4, 9, 16 note that you use “nditer”

Answer 180

* # transpose; permutes the dimensions of an array * # concatenate; joins a sequence of arrays along an existing axis * # append; appends the values to the end of an array

Answer 181

it starts as.. array([[1, 2], [3, 4]]) and transpose will change the dimensions of the array (flip rows and columns) so after np.transpose(a) we have… array([[1, 3], [2, 4]])

Answer 182

by rows you would…. np.append(a, b, axis = 0) #axis 0 for rows result… array([[2, 2], [3, 3], [4, 4], [6, 6]]) and for columns… np.append(a, b, axis = 1) #axis 1 for columns. result…. array([[2, 2, 4, 4], [3, 3, 6, 6]])

Answer 183

a = np.zeros((3, 3)) print(a) [[0, 0, 0] [0, 0, 0] [0, 0, 0]]

Answer 184

x = np.full((3, 3), 42) print(x) [[42, 42, 42] [42, 42, 42] [42, 42, 42]]

Answer 185

e = np.random.random((2, 2))

Answer 186

first we find -3, which is number 7 then we go from -3 until 3 which happens to be number 3 as it is in the 4th location in the row (0, 1, 2, 3) and lastly we return the values in OPPOSITE order because of -1 array([7, 6, 5, 4])

Answer 187

* NumPy = First, ROW, Second, COLUMN * Pandas = First, COLUMN, Second ROW

Answer 188

Multiple rows can be selected using ’:’ operator as in numpy arrays df[1:3] just remember that in Pandas, you pick COLUMN FIRST, and row second

Answer 189

if the file name is titanic.csv titanic.info() will return

Answer 190

if the file name is titanic.csv titanic.describe()

Answer 191

* titanic.hist( * bins = # the width of bars (lower is wider) * figsize=(16, 9) #is the proportions of the figures * grid=False #whether you want a grid or not * plt.show() #and then show the histogram

Answer 192

titanic. Age.hist(bins = 50, figsize=(12, 6), grid=True) plt. xlabel(‘Age’) plt. ylabel(‘Number of people’) plt. show()

Answer 193

No… NaN == NaN is False NaN is special in that it doesn't have a real value, so comparing it to itself doesn't return true. Essentially, NaN is equal to nothing, not even NaN Because of this, the only safe way to tell whether or not a value is missing in a DataFrame is by using the isnull() function. Indeed, this function can be used to filter rows with missing values; edu[edu["Value"].isnull()]

Answer 194

* COLUMNS * are Series, which consists of several values, where each value has an index * ROWS * have a specific index to access them and be any name or value

Answer 195

when not specifying the index, they will simply be a sequence of integers starting from 0. 0, 1, 2, 3 in this case

Answer 196

Helps show the first (by default = 5) rows in a dataset so we can see how the data looks. If you insert a number in head(), you will get that number of rows instead of the default 5 rows. The tail() method is the opposite in the way that it gives you the LAST 5 rows.

Answer 197

filename.columns and filename.index

Answer 198

edu[10:14] will provide the rows from 10th to 13th position BUT this does not take your index labels into account. Only the position. edu.loc[10:14] will return the values of all the rows between the row labeled 10 and the row labede 14. This could be 10,11,12,13,14 but it could just as well be only one value OR it could be many values. It could also be a row which is indexed 100 if that row has been placed between the rows labeled 10:14.

Answer 199

axis = 0 finds the maximum value for each column (finding max within the rows for each column) while axis = 1 find the maximum value for the row (finding max within the column for each row)

Answer 200

In Python ,NaN values propagate through all operations without raising an exception. In contrast, Pandas operations exclude NaN values representing missing data. For example, the pandas max function excludes NaN values, thus they are interpreted as missing values, while the standard Python max function will take the mathematical interpretation of NaN and return it as the maximum:

Answer 201

It is essentially just a function without a name. It is written in-line. For example…

Answer 202

we are defining a new column called ‘ValueNorm’ by taking ‘Value’/the highest number in the ‘Value’ column lastly we ask to see the 5 last rows of the updated DataFrame using tail()

Answer 203

using the append function, which receives as argument the new row represented as a dictionary where the keys are the name of the existing columns and the values the associated values. It is important to the the ignore\_index flag to True, otherwise the index 0 is given to this new row which will produce an error if it already exists (may potentially overwrite if not set to True)

Answer 204

simply use the drop and max functions. Why max? because then we will be taking the last row if the index is ordered at least.

Answer 205

using fillna() eduFilled = edu.fillna(value={‘Value’:0}) will fill in the NaN with 0 instead but be careful about doing so will change the statistics of your data when using pandas.

Answer 206

here we are using the sort function to sort the data by ‘Value’ and NOT in ascending order (then it must be descending order), meaning that we will get the 5 highest values as we use edu.head() which by default give 5 rows.

Answer 207

here we are using groupby to group some data. we are clearly interested in GEO (countries) and the values. We are grouping by Geo (country) and asking for the mean of values for each country. next, we ask pandas to sort this data by values in a descending order.

Answer 208

1. first we are filtering the data with a boolean expression asking for data dated later than 2005 from the TIME column 2. secondly, we use the pd.pivot\_table function to rearrange our data such that the index/rows become GEO/countries and columns will be equal to time (the time values newer than 2005 as we are using the filtered data) 3. lastly we ask to see the first 10 rows

Answer 209

obviously we could just write 19 + y and get 22 we could also press the arrow key up in command and pick up x + 10 and add + y to get 22 the most correct and simplest way though is: \_ + y #underscore + y 22

Answer 210

* list =[] * most flexible and can be both numbers and strings * set = {} * like list BUT… will not maintain sequence and does not support duplicate values * tuple = () * tuples you cannot change the values the same way as lists. Thus, use only tuples for things that are fixed. * tuples are though useful because they are faster for python to run

Answer 211

* None * Numeric * Int, float, complex, bool * List [] * Tuple () * set {} * string “” * range (2,10,2) * Dictionary

Answer 212

2 \* 3 = 6

Answer 213

computers think binary.. 11001 1\*(2^4), 1\*(2^3), 0\*(2^2), 0\*(2^1), 1\*(2^0) = 25

Answer 214

* complement (∼) (‘tilde’ symbol) * and (&) * Or (І) * XOR (^) * Left shift (\<\<) * right shift (\>\>)

Answer 215

because.,.., 10 is in binary…. 1010 meaning that it is essentially 1010.000000000 (infinite number of 0s after the decimal) now we shift 2 to the left so we get 101000.00000 and thus 101000 1\*32, 0\*16, 1\*8, 0\*4, 0\*2, 0\*1 = 40

Answer 216

because… 100 is in binary 1100100 meaning that it is essentially 1100100.000000(all the 0 in the world if needed) now we shift 3 to the right so it is now.. 1100.100 and thus 1\*8, 1\*4, 0\*2, 0\*1 = 12

Answer 217

using math.floor and math.ceil (after importing math, import math to python) is essentially round numbers to the nearest integer floor or ceiling. for 2.7, the floor is 2 and ceiling is 3 for 100.14 the floor is 100 and ceiling is 101

Answer 218

if i in range(5): if i == 3: break print(“Hello “, i) with break it will stop printing so we only get; Hello 0, Hello 1, Hello 2 if i in range(5): if i == 3: continue print(“Hello “, i) with break it will CONTINUE printing so we only get; Hello 0, Hello 1, Hello 2, Hello 4,

Answer 219

To make a for-loop in which you have an if-elif-else statement WHERE the “else” IS NOT indented.

Answer 220

You use TypeCode to specify which type the values are of for an ARRAY import array array.array(‘b’, [5, 7, 8, 10])

Answer 221

For multi-dimensional arrays

Answer 222

1. array() 1. arr = array([1, 2, 3, 4, 5]) 2. linspace() 1. arr = linspace(0, 16, 32) 1. start, stop and step/parts (BUT.. step is splitting up into parts here) 1. from 0 to 16 and split into 32 numbers. 2. if not specifying the number of parts it is 50 by default 3. logspace() 1. arr = logspace(1, 40, 5) 1. start, stop and parts/step 1. split up to 5 numbers between 1 and 40 according to log 4. arrange() 1. arr = arange(1, 15, 2) 1. will return… 1, 3, 5, 7, 9, 11, 13 2. start, stop and STEP 5. zeros() 1. arr = zeros() 1. array of ALL 0s 2. fx arr = zeros(5) will return [0, 0, 0, 0, 0] 6. ones() 1. arr = ones() 1. array of ALL 1s

Answer 223

print(arr1.ndim)

Answer 224

print(arr.nshape)

Answer 225

print(arr.size)

Answer 226

essentially an anonymous function = a function with no name

Answer 227

#it is a special variable in python used to avoid running an entire #module when trying to call a function from an external library/module #that you have imported

Answer 228

Class are overall.. class Computer: and then the methods/functions are part of that class and must be called with… computer.config(com1) just as we write numpy.something but.. you can actually also write… com1.config() which is more likely what you will see (calling the method FROM the object)

Answer 229

thinking in objects just like everything we need to do in real life we need "objects" for such as a laptop, a camera, a frying pan etc. in programming we need to build objects also and put them together what matters is DESIGNING objects, not manufacturing them as that can be done anywhere, and in the computer world they can be replicated billions of times quickly.

Answer 230

Class A: Class B(A): Class C(B): but we can also say that C is inheriting from A and B (mom and dad) who are unrelated by… Class A: Class B: Class C(A, B)

Answer 231

polymorphism = poly(many) morphism(forms) = objects can take many forms. It can behave in multiple ways. duck typing operator overloading method overloading method overriding

Answer 232

method overloading: if you have two methods with the same name, def average(a,b) and def average(a, b, c) it is method overloading one takes two parameters and one takes three

Answer 233

two methods with the same name AND the same number of parameters also, if class B(A): inherits what is in A, but B has something itself, it will override the information from A. Say class A: contains the car of your dad Say class B(A): contains nothing, then your father's car is yours(inheritance) but if you have your own car within B, it will be that one.

Answer 234

when your code returns a value but the value is wrong. if 3+2 returns 4, you have made a logical error

Answer 235

when the code does not work during part of the run time… this is for example if people put in a string and you only allow for integers, float when only integers allowed, if a negative value or if divided by 0 and so forth.

Answer 236

use the try: except: #can use multiple excepts except: except: finally: setup….

Answer 237

It is actually both… * Compiled language * the computer does not understand the language so we compile the code we write for the computer to understand in binary form (0101010101010110110) * Interpreted language * also interpreted as… * source code =\> compiled =\> byte code =\> interpreted by python virtual machine =\> machine learning * it is taking things line by line

Answer 238

a = 8 b = 10 then… a = c # now c is 8 b = a #now a is 10 c = b #now b is 8 a = 10 b = 8

Answer 239

del(areas[-4:-2])

Answer 240

The problem we have is that area\_copy = areas is not explicit enough in copying the areas list. Thus, when we change the values of areas\_copy[] to 5 we are in fact also changing the value [0] in the original areas list. To avoid changing the original list when making changes in the copy, we must use either list(areas) or areas[:]

Answer 241

you can always search the internet but otherwise use.. help(function\_name) so for example help(max), help(sorted) and so forth

Answer 242

there are different methods available to different types of objects. also, sometimes the same method is available to different types of objects but behave differently,. #... METHODS call functions on objects fam.index()

Answer 243

place\_up = place.upper() print(place) print(place\_up) poolhouse POOLHOUSE

Answer 244

areas. append(24.5) areas. append(15.45)

Answer 245

* the ARRAY is able to perform calculations on the entire set of values * You can also use boolean operators to obtain results from arrays.

Answer 246

Array cannot contain different value types. If having different value types, type coercion will take place

Answer 247

print(np\_baseball[49])

Answer 248

np\_weight\_lb = np\_baseball[:, 1]

Answer 249

NOTE that the format is…. np.builtinfunction(nameofarray) and… rememebr that NumPy has ROW first, column second so [:, 0]

Answer 250

Heights of the goalkeepers: gk\_heights gk\_heights = np\_heights[np\_positions == 'GK'] Heights of the other players: other\_heights other\_heights = np\_heights[np\_positions != 'GK']

Answer 251

import matplotlib.pyplot as plt

Answer 252

plt. plot(x, y) = line plot plt. scatter(x, y) = scatter plot (no lines, just data points)

Answer 253

plt. xscale('log') #changing the x-axis to logarithmic plt. show()

Answer 254

import matplotlib.pyplot as plt plt.hist(dataname, bins = 10) #it is 10 by default

Answer 255

plt. xlabel(‘price’) plt. ylabel(‘quantity’)

Answer 256

plt.title(‘my title here’)

Answer 257

for example.. plt.yticks([0, 2, 4, 6, 8, 10])

Answer 258

tick\_val = [1000, 10000, 100000] tick\_lab = ['1k', '10k', '100k'] plt. xticks(tick\_val, tick\_lab) plt. show()

Answer 259

* We are making a scatter plot * with gdp\_cap on the x-axis * and life\_exp on the y-axis * size is set to np.array(pop) \* 2 #doubling the sizes of the bubbles * c = col =\> colors are set acording to what has been defined in col which in this case is different colors depending on continent of origin * alpha = 0.8 sets the opacity/transparency of the bubbles. 0 = 100 % opacity

Answer 260

We can add text with plt. text(1550, 71, ‘India’) plt. text(5700, 80, ‘China’) we obviously need to know these values first.

Answer 261

print(europe.keys()) dict\_keys(['spain', 'france', 'norway', 'germany'])

Answer 262

print(europe['norway']) oslo

Answer 263

List * If you want to easily access values in an ordered matter (using indexes) Dictionary * When you want more freedom and have a unique table in which the unique keys can take different forms

Answer 264

europe['italy'] = 'rome’ now ask.. europe(‘italy’ in europe) True

Answer 265

print(europe['france']['capital'])

Answer 266

row\_labels = ['US', 'AUS', 'JPN', 'IN', 'RU', 'MOR', 'EG'] cars.index = row\_labels

Answer 267

cars = pd.read.csv(‘cars.csv’) #remember ‘’ around the file name print(cars)

Answer 268

The single bracket version gives a Pandas SERIES while the double bracket version gives a Pandas DataFrame.

Answer 269

loc = label-based meaning that you have to specify rows and columns based on their row and column labels. iloc = integer index based so you have to specify rows and columns by their integer index starting from 0.

Answer 270

We ask for the rows indexed 3 and 4, and then the column indexed 0. we get it as a DataFrame because of [[]]

Answer 271

Print sub-DataFrame print(cars.loc[['RU', 'MOR'], ['country', 'drives\_right']])

Answer 272

print(cars.loc[:,['drives\_right']]) can also be done with iloc if we know the index number of the drives\_right column

Answer 273

True Because Python determines the relationship based on alphabetical order when working with strings.

Answer 274

Arrays work slightly differently so you need to use the AND, OR, NOT equivalent functions in NumPy, which are: * np.logical\_and() * np.logical\_or() * np.logical\_not() Example: np.logical\_and(my\_house \< 11, your\_house \< 15)

Answer 275

use for loop + enumerate

Answer 276

Key values in dictionary * for key, val in my\_dict.items(): * #use .items

Answer 277

elements in an array * for val in np.nditer(my\_array): * #use np.nditer

Answer 278

for pandas Dataframes * for lab, row in brics.iterrows(): * #use .iterrows()

Answer 279

Key values in dictionary * for key, val in my\_dict.items(): * #use .items elements in an array * for val in np.nditer(my\_array): * #use np.nditer for pandas Dataframes * for lab, row in brics.iterrows(): * #use .iterrows()

Answer 280

(already set as “lab” and “row”)

Answer 281

use .apply very important feature. .apply

Answer 282

Returning values is generally more desirable than printing them out because, as you saw earlier, a print() call assigned to a variable has type NoneType.

Answer 283

Using tuples!!

Answer 284

* GLOBAL scope * defined in the main body of a script * LOCAL scope * defined inside a function * BUILT-IN scope * names in the pre-defined built-ins module (such as ‘print’) * NOTE; you need tim ‘import builtins’ to use this. * writing ‘dir(builtins)’, you can see all builtin functions Python ALWAYS search for a value in LOCAL scope first, second GLOBAL scope and lastly BUILT-in scope.

Answer 285

Here echo=1 =\> echo is set to 1 unless otherwise specified. Thus, in line 13, we do not specify echo but it will return 1 time, while in line 15, we ask it to return 5 times

Answer 286

Use (\*args) #single \* It will turn a tuple of values. def\_sums(\*args):

Answer 287

Use (\*\*kwargs) #double \*\* It will turn a dictionary of values def report\_status(\*\*kwargs):

Answer 288

try: return: except: and… if ‘something’: raise \_\_\_\_\_Error(‘explanation’) try: return except: \_\_\_\_\_Error

Answer 289

Iterable * An object with an associated iter() method * Examples: lists, strings, dictionaries, file connections * Applying iter() to an iterable creates an iterator Iterator * Produces next value with next()

Answer 290

use.. print(\*it)

Answer 291

It returns an enumerate object that produces a sequence of tuples, and each of the tuples is an index-value pair.

Answer 292

It takes any number of iterables and returns a zip object that is an iterator of tuples. If you want to print the values of a zip object, you need to convert it to a list and then print it.

Answer 293

Because there can be too much data to hold in memory. pandas function: read\_csv() * specify the chunk with… chunksize read\_csv(‘filename’, chunksize=xxxx)

Answer 294

uses () Great for very big numbers as it does not store everything in memory (as a list comprehension would do). While a list comprehension produces a list as output, a generator produces a generator object.

Answer 295

! ls will display the contents of your current directory.

Answer 296

* Text files containing records * Table data * Record: row of fields or attributes * Column: feature or attribute Flat files often have headers .csv, .txt (tab-delimited),

Answer 297

* np.loadtxt(filename, delimiter=‘,’) * digits = np.loadtxt(file, delimiter=', skiprows = 1') * ‘,’ for comma-separated * ‘\t’ for tab-delimited * skiprows = 1 will skip the first row if we have headers for example * usecols =\> lets you specify which rows wish to keep * np.genfromtxt(‘filename’, delimiter = ‘,’, names=True, dtype=None) * To be used when you have different data-types (strings, float, etc). * names = True =\> means there is a header * np.recfromcsv() * Behaves similarly to np.genfromtxt BUT has default dtype=None, default ‘,’ as delimiter and default names=True.

Answer 298

* Two-dimensional labeled data structures * Columns of potentially different types * Manipulate, slice, reshape, groupby, join, merge * Perform statistics * Work with time series data * Pandas is for data analysis and modeling.

Answer 299

pd.read\_csv(filename, **_sep = ‘\t’_**, comment = ‘#’, na\_values = ‘Nothing’)

Answer 300

* A file type native to python * Not readable by humans but readable by python/machines * JSON files are an option if you want it readable by humans * Motivation; many datatypes for which it isn’t obvious how to store (such as lists, dictionaries etc.) * ‘rb’ means read only binary

Answer 301

figureo ut what the sheets in excel are called by print(data.sheet\_names) here as the file has been set to ‘data’ and to make dataframes of those sheets, use .parse and the sheet name OR sheet index

Answer 302

very important for data science used for: * advanced analytics * multivariate analysis * business intelligence * data management * predictive analytics * standard for computational analysis

Answer 303

* Hierarchical Data format Version 5 * Standard for storing large quantities of numerical data. * hundreds of gigabytes or terabytes (can scale to exabytes)

Answer 304

* Matrix Laboratory * Industry standard in engineering and science scipy. io.loadmat() = read .mat files scipy. io.savemat() = write .mat files

Answer 305

* Based on relational model of data * Rows are ordered and the columns are attributes for the information in the rows * Each row need a primary key column that has a unique entry for each row that we can call information from (such as OrderID, CustomerNumber, EmployeeNumber etc.)

Answer 306

get data out of the database

Answer 307

1. Import create\_engine 2. import pandas as pd 3. Create the engine 4. Connect to the engine 5. Write a query (select \* =\> imports all columns) 6. Turn the query into a DataFrame using fetchall() 7. Close the connection

Answer 308

It is possible to skip the step of saving it locally (line 8-9) and just plug in the url directly in pd.read\_csv so: df = pd.read\_csv(url, sep=';')

Answer 309

Uniform/Universal Resource Locator

Answer 310

* Parse and extract structured data from HTML * “Make tag soup beautiful and extract information”

Answer 311

* Application Programming Interface * Protocols and routines that build and interact with software applications * allows two software programs to communicate with each other

Answer 312

* JavaScript Object Notation * Real-time server-to-browser-communication * It is readable by humans * loads as a dictionary {}

Answer 313

the json() method so… url = 'https://en.wikipedia.org/w/api.php?action=query&prop=extracts&format=json&exintro=&titles=pizza' Package the request, send the request and catch the response: r r = requests.get(url) Decode the JSON data into a dictionary: json\_data json\_data = r.json()

Answer 314

* Inconsistent column names * Missing data (NaN) * Outliers * Duplicate rows * Untidy * Need to process columns * Column types can signal unexpected data values

Answer 315

* df.columns() #to get column names * df.head() #first 5 rows by default * df.tail() #last 5 rows by default * df.shape() #shape of dataframe with (rows,columns) * df.info() #various info about the dataframe, non-missing values, data type etc. * df.describe() #getting basic statistics ONLY on numeric columns

Answer 316

whether the data is numeric or not, you can use .value\_counts(dropna=False) dropna=False is important to add to see missing values (NaN) note that it is value\_counts with s

Answer 317

import matplotlib.pylot as plt * df['Existing Zoning Sqft'].plot(kind='hist', rot=70, logx=True, logy=True) #here setting both x and y axis as logarithmic * df.boxplot(column='initial\_cost', by='Borough', rot=90) # comparing inital\_cost column across different values of the Borough column * great for numeric values to be compared across different categories * df.plot(kind='scatter', x='initial\_cost', y='total\_est\_fee', rot=70) * great for visiualizing two numeric columns plt.show()

Answer 318

* Columns represent separate variables * Rows represent individual observations * Observational units form tables Tidy data makes it easier to fix common data problems

Answer 319

* We are melting columns except ‘month’ and ‘day’ * we call the value-column = reading * and the variable column = measurement * Melting turns columns into rows

Answer 320

turn unique values into separate columns why: * analysis friendly shape to reporting friendly shape While melting takes a set of columns and turns it into a single column, pivoting will create a new column for each unique value in a specified column.

Answer 321

Pivoting such that * we do not change the two columns ‘month’ and ‘day’ * we change the ‘measurement’ column and split the unique values in this column into new columns * and take the values from ‘reading’ and plug them into those rows

Answer 322

\_ serves as a delimiter we can use .split()

Answer 323

#concatenating ROWS pd.concat([firstset, secondset, thirdset, etcset], axis=0) #Concatenating COLUMNS pd.concat([firstset, secondset, thirdset, etcset], axis=1) NOTE… Data MUST be in a list to concatenate DataFrames.

Answer 324

pattern matching for file names wildcards: \*? * any csv file: \*.csv * any single character: file\_?.csv

Answer 325

pd.merge(left=dd, right=dd\_d, on=None, left\_on=’something’, right\_on=’something) example: two dataframes; visited and site with columns that are the same called “site” and “name” o2o = pd.merge(left=site, right=visited, left\_on='name', right\_on='site') Many-to-many data merge ; The final merging scenario occurs when both DataFrames do not have unique keys for a merge. What happens here is that for each duplicated key, every pairwise combination will be created.

Answer 326

print(df.dtypes)

Answer 327

This will lower the memory need

Answer 328

df.drop\_duplicates() Important to delete duplicate values as they take up a lot of memory and cause unneeded calculations to be performed when processing data

Answer 329

1. We have a dataset, ‘gapminder’ with 780 rows and 218 columns 2. each column represent a year with life expectancy data 3. but the very first column [0] has the country names 4. we then melt the data such together such that we get rows instead of columns = one row will have a year value, the life expectancy and the associated country 5. we make sure not to touch the country life by putting ‘life expectancy’ in as id\_vars 6. we then rename the columns to ‘country’, ‘year’ and ‘life\_expectancy’ 7. and print the head of it

Answer 330

1. df.plot(kind=’hist) 2. iris.plt.hist() 3. iris.hist() NOTE they have different syntax

Answer 331

print(df.quantile([0.05, 0.95])

Answer 332

df[‘wind\_speed’] = pd.to\_numeric(df[‘wind\_speed’], errors=’coerce’)

Answer 333

august\_2011\_high = august\_2011.loc[august\_2011 \> august\_max] loc with boolean condition both august\_2011 and august\_max are already encoded as variables

Answer 334

df[‘eggs’] returns a series (one-dimensional labeled data) df[[‘eggs’]] returns a DataFrame

Answer 335

df. index.name = ‘MONTHS’ df. columns.name = ‘PRODUCTS’ just as you set the index names by.. df.index = [‘Jan’, ‘Feb’, ‘Mar’, ‘Apr’]

Answer 336

Set the index to be the columns ['state', 'month']: sales sales = sales.set\_index(['state', 'month']) Sort the MultiIndex: sales sales = sales.sort\_index() Print the sales DataFrame print(sales)

Answer 337

No… you will have to unstack the multi-index by turning an index to a column first. df.unstack(level=’indexcolumnname’) or df.unstack(level=1) #to remove the second index

Answer 338

swapped = df.swaplevel(0, 1) swapped.sort\_index()

Answer 339

standardized = gapminder\_2010.groupby('region')['life','fertility'].transform(zscore)

Answer 340

* idxmax() * Row or column label where maximum value is located * idxmax(axis=’columns) #for columns * idxmin() * Row or column label where minimum value is located * idxmin(axis=’columns) #for columns

Answer 341

You can achieve this using Categorical types. Redefine the 'Medal' column of the DataFrame medals as an ordered categorical. To do this, use pd.Categorical() medals.Medal = pd.Categorical(values=medals.Medal, categories=['Bronze', 'Silver', 'Gold'], ordered=True)

Answer 342

use a loop…. Create the list of three DataFrames: dataframes dataframes = [] for filename in filenames: dataframes.append(pd.read\_csv(filename))

Answer 343

inplace = True is by default false. When True, we change the current dataframe when not set, and thus false by default, we create a new dataframe with a column missing. so… we get multiple dataframes, which is slower and often quite useless.

Answer 344

we are changing the str ‘Nowhere’ to ‘A city’ and overwrite the current DataFrame as we set inplace=True.

Answer 345

eu\_metro\_areas.to\_csv('My\_metro\_areas.csv', sep=',')

Answer 346

eu\_metro\_areas.to\_excel("My\_metro\_areas.xlsx")

Answer 347

it will show small bars for each observation/datapoint in the graph so we understand how big the dataset is

Answer 348

df[‘newcolumnname’] = [‘list’, ‘of’, ‘values’, ‘for’, ‘new’, ‘column’]

Answer 349

* .append() * stacking vertically * pd.concat() * stacking many horizontally or vertically * simple inner/outer joins on indexes * df.join() * inner, outer, left, right joins on indexes * pd.merge() * many joins on multiple columns