Importing dataset

Question 1

Importing

Answer 1

import pandas as pd

Question 2

Read the online file

Answer 2

# Import pandas library
import pandas as pd

# Read the online file by the URL provides above, and assign it to variable "df"
o
ther_path = "https://cf-courses-data.s3.us.cloud-object storage.appdomain.cloud/IBMDeveloperSkillsNetwork-DA0101EN-SkillsNetwork/labs/Data%20files/auto.csv"

df = pd.read_csv(other_path, header=None)

Question 3

header = none

Answer 3

we can add an argument headers = None inside the read_csv() method, so that pandas will not automatically set the first row as a header.

import pandas as pd
url = xxxxx
df = pd.read_csv(url, header=None)

Question 4

Print the first 5 rows

Answer 4

df.head(5)

Question 5

Print the bottom 10 rows

Answer 5

df.tail(10)

Question 6

You need to define the headers first and then print the first 10 rows

Answer 6

df. columns = headers

df. head(10)

Question 7

Remove missing values

Answer 7

df1=df.replace(‘?’, np.NaN)

Question 8

Drop missing values along the column “price”

Answer 8

df=df1.dropna(subset=[“price”], axis=0)

df.head(20)

Question 9

Print columns

Answer 9

print (df.columns)

Question 10

Print data types

Answer 10

print(df.dtypes)

Question 11

Describe all teh main characteristics of teh data

Answer 11

# describe all the columns in "df" 
df.describe(include = "all")

Question 12

Describe certain columns

Answer 12

df [[‘length’, ‘compression-ratio’]].describe()

Question 13

Export to different formats in Python

Answer 13

data format: csv

read: pd.read_csv()
save: df.to_csv()