Pandas Flashcards

1
Q

Write the code that is required to run pandas

A

import pandas as pd

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2
Q

Read in a csv file into pandas given

import pandas as pd

A

pd.read_csv(‘myfile.csv’)

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3
Q

Read in a excel file into pandas given

import pandas as pd

A

pd.read_excel(‘my_file.xlsx’)

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4
Q

Read in a json file into pandas given

import pandas as pd

A

pd.read_json(‘my_file.json’)

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5
Q

What is pd in import pandas as pd?

A

an alias

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6
Q

Read in a DataFram file into pandas given

import pandas as pd

A

pd.DataFrame.from_dict(‘my_file.???)

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7
Q

What is the syntax to export DataFrame to other formats?

A

df.to_csv(‘my_file.csv’)
df.to_excel(‘my_file.xslx’)
df.to_json(‘my_file.json’)
df.to_dict(‘my_file.???’)

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8
Q

True or False

like MS Excel, Pandas handles spreedsheet like data called a DataFrame

A

True

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9
Q

.txt stands for?

A

tab separated file, known as a text file.

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10
Q

.csv stands for?

A

comma separated file, known as a spreadsheet

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11
Q

.xlsx stands for?

A

Microsoft Excel Open XML Spreadsheet

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12
Q

.json stands for?

A

JavaScript Object Notation

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13
Q

What is a delimiter in Pandas?

A

Commas is excel type files are delimiters they separate the data, in Pandas you can detrimine what is going to be used to separate the data being loaded in such as ‘\t’ in .txt files

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14
Q

Write the code to read in headers

A

df.columns( )
print(df.columns)

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15
Q

Code to read in a specific column

A

df. ([‘Name’])
df. Name

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16
Q

Code to read in a specific column limited rows

A

df.Name[0:5]

name column rows 0 - 4

17
Q

Code to read in a number of columns

A

df[[‘Name’, ‘Attack’, ‘Defense’]]

as a list of col names

18
Q

iloc stands for?

A

integer location

19
Q

Code to read in a specific DataFrame row

A

df.iloc[17]

20
Q

Code to read in a multiple DataFrame rows

A

df.iloc[2:10]

rows 2 - 9

21
Q

What will this return in a Pandas DataFrame?

df.iloc[2,1]

A

df.iloc[row, col]

22
Q

What does this code achieve?

for index, row in df.iterrows():
print(index, row[‘Name’])

A

traverses through all the DataFrame rows based on the Name col

23
Q

loc stands for?

A

is a labeled based location

good for using conditional statements

24
Q

What does this code return in a Pandas DataFrame?

df.loc[df[‘Type 1’] == ‘Fire’]

A

returns only those records whose Type 1 attribute is labeled Fire

25
Q

What does this code return in a Pandas DataFrame?

df.loc[df[‘Defense’] < 25]

A

returns only the records where the Defense is less than 25

26
Q

What does this code provide?

df.describe()

A

high-level numerical stats on the DataFrame

27
Q

This code will return what?

df.sort_values(‘Name’)

A

sorted DataFrame by Name col in descending order

28
Q

How would you make this sort descending order instead of the default ascending?

df.sort_values(‘Name’)

A

df.sort_values(‘Name’, ascending = False)

29
Q

What does this code return in a Pandas DataFrame?

df.sort_values([‘Type 1’, ‘HP’])

A

both columns are sorted by alpha and numeric ascending order

30
Q

What does this code return in a Pandas DataFrame?

df.sort_values([‘Type 1’, ‘HP’], ascending=[0, 1])

A

ascending is set to False, True based on the two cols ‘Type 1’ and ‘HP’

31
Q

What is this code doing?

df[‘New Column’] = df[‘HP’] + df[‘Attack’] + df[‘Defense’] + df[‘Speed’]

A

adding a New Column to the df with concatenated values from the cols HP, Attack, Defense, and Speed.

32
Q

df.head( ) returns what?

A

First 5 rows of the DataFrame

33
Q

df.tail( ) returns what?

A

Last 5 rows of a DataFram

34
Q

df.colums( ) returns what?

A

All the cols in the DataFrame

35
Q

This code is performing what action?

df = df.drop(columns=[‘New Column’])

A

dropping the New Column and setting it to the df

36
Q

Given this code how many rows will be returned?

df.iloc[:,]

A

all them

df.iloc[rows : , cols :]