idek what chapter

Question 1

Series vs. DataFrames

Answer 1

series= 1d arrays
dataframes = 2d arrays
each of which have rows and columns which can be labelled

Question 2

how to create series or dataframe

Answer 2

use python dictionary

Question 3

define a dictionary

Answer 3

structure but mapping type (not a data sequence, so is indexed using keys)

is of type dict

mutable!

Question 4

how to create a dictionary?

Answer 4

key-value pairs separated by commas, put in CURLY BRACKETS
bigguy = {‘keyname’:value_inside_key, ‘biggestguy’:’masonReilly}

Question 5

how to index in a dictionary

Answer 5

dictionary[‘keyname’]
error if keyname DNE or index using integers

Question 6

dictionary = mutable or not?

Answer 6

mutable (including modifying things inside it)

Question 7

how to add/remove values to dictionary

Answer 7

dictionary[‘newkeyname’] = 123453241

del dictionary[‘nameofthingimremoving’]

Question 8

len(mydictionary) returns?

Answer 8

amnt of key pairs

Question 9

list(mydictionary) returns?
‘year’ in mydictionary returns?

Answer 9

returns the list equivalent
returns whether or not a key of that name exists in the dictionary

Question 10

mydictionary = {‘year’:2313, ‘big’:’mason reilly’}
mydictionary.get(‘size’)
mydictionary.get(‘size’, -999)
mydictionary.get(‘big’}
what will these two getters return?

Answer 10

1. None
2. -999
3. ‘mason reilly’

Question 11

mydictionary.get()

Answer 11

mydictionary.get(‘keyname’)
mydictionary.get(‘keyname’, thing if keyname is not in dictionary)

Question 12

why is get better than indexing a keyname?

Answer 12

indexing will return an error, get will return a value

Question 13

dictionary pop

Answer 13

mydictionary.pop(‘name’)
mydictionary.pop(‘name’, thing if name DNE)

removes and returns removed value

error if no thing for DNE is specified and name DNE

Question 14

dictionary popitem

Answer 14

mydict.popitem()
removes and returns last key of dictionary as a tuple

Question 15

dictionary clear

Answer 15

mydict.clear()
clears all key-pairs from dictionary

Question 16

keys
values
items

Answer 16

mydict.keys()
mydict.values()
mydict.items()

all used to iterate, returns VIEW OBJECTS of the certain things

keys returns a view object list of the names
values returns values list

items returns keys and values respectively, need 2 iterators to work with them

Question 17

how to store multiple dictionaries

Answer 17

list of dictionaries

Question 18

can you have data sequences inside of dictionaries?

Answer 18

duhh

Question 19

how would you do a dictionary comprehension?

Answer 19

mydict = {i:i**3 for i in range(5)}
each of these adds a new key-value pair

Question 20

do key names have to be strings?

Answer 20

nah

Question 21

should you import pandas with numpy? why?

Answer 21

yes, bcz its built on nump-y

Question 22

What is a Pandas Series?

Answer 22

1d array created using a list or array

Stored as a NumPy array, can index it and slice it just like every other array

Question 23

what does this return:
numseries = pd.Series([11, 2, 3, 5])
numseries

Answer 23

0 11
1 2
2 3
3 5
dtype: int64
indices, actual data passed, AND dtype are stored in variable!

Question 24

how to access just the numbers in Series?

Answer 24

numseries.values
returns
array([11, 2, 3, 5])

Question 25

values

Answer 25

numseries.values
array([11, 2, 3, 5])

returns the non-index, non type, actual values stored in the Series.

Question 26

can you use index on a series?

Answer 26

yes, but itll just give you the start index the end index and the steps between each index

Question 27

create a series with indices a, b, c, d

Answer 27

mystuff = pd.Series([1, 2, 3, 4], [‘a’, ‘b’, ‘c’, ‘d’])

these new indices can be used to index and slice into the series

numlabels[‘b’:’d’] returns

b 2
c 3
d 4
dtype int64

Question 28

do specified indices work inclusively on all or like normal python?

Answer 28

inclusively on all, only the OG default integer indice slicing does not include the last index

Question 29

can you make a series into a dictionary?

Answer 29

yes!
typecast whatever dictionary you want and youll get the indexes as the names and the values as the values with the little dtype at the bottom

Question 30

wtf is a DataFrame

Answer 30

2d array with labels for rows and columns

Question 31

make a dataframe

Answer 31

dataf = pd.DataFrame(myseries, columns = [‘name of first column’])