Libraries - pandas

Question 1

Import the pandas library

Answer 1

import pandas as pd

Question 2

Store the data from a csv file called “stats.csv” (which is saved in the same directory as the script) and store it in the variable “df”

“df” stands for DataFrame

Answer 2

df = pd.read_csv(“stats.csv”)

Question 3

pd.read_csv(“example”.csv)

Explain the data structure pandas uses to store the data from “example.csv”

Answer 3

pandas ESSENTIALLY uses a dictionary where column headers are the keys, and the values of each key are a List of the data from the “rows” under each key.

However, pandas also assigns an index number to each of the items in each List of data.

Essentially you just need to remember that the “keys” are like the column letters in Excel, and the index numbers assigned to the values are like the row numbers in Excel (tho index # starts from “0”)

Question 4

A pandas DataFrame is stored in varable “df”

Preview the first 5 “rows” in the terminal

Answer 4

print(df.head())

This print only to “top” 5 rows

Question 5

A pandas DataFrame is stored in varable “df”

Preview the last 5 “rows” in the terminal

Answer 5

print(df.tail())

Question 6

A pandas DataFrame in variable “df” has a date column with the key-header “date”

Convert this date column to the datetime formatt

Answer 6

df[‘date’] = pd.to_datetime(df[‘date’])

Question 7

A pandas DataFrame in variable “df” has a date column with the key-header “date”

The date column has been converted to datetime

Print all the month numbers to the terminal

Answer 7

df[‘date’].dt.month

Question 8

A pandas DataFrame in variable “df” has a date column with the key-header “date”

The date column has been converted to datetime

Create a new column called “month” showing the month name only

Answer 8

df[‘month’] = df[‘date’].dt.month_name()