Reading CSV files with read_csv in Pandas - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to read a CSV file named 'data.csv' into a DataFrame.

Pandas

import pandas as pd
df = pd.[1]('data.csv')

Drag options to blanks, or click blank then click option'

Aread_table

Bread_excel

Cread_json

Dread_csv

Attempts:

3 left

💡 Hint

Common Mistakes

Using read_excel instead of read_csv

Using read_json which is for JSON files

Using read_table which expects tab-separated files

The read_csv function is used to read CSV files into a pandas DataFrame.

2fill in blank

medium

Complete the code to read 'data.csv' but only load the first 5 rows.

Pandas

import pandas as pd
df = pd.read_csv('data.csv', [1]=5)

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Anrows

Brows

Chead

Dlimit

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'head' which is a method on DataFrames, not a parameter

Using 'rows' or 'limit' which are not valid parameters

The nrows parameter limits the number of rows read from the CSV file.

3fill in blank

hard

Fix the error in the code to read a CSV file with a semicolon separator.

Pandas

import pandas as pd
df = pd.read_csv('data.csv', sep=[1])

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A,

B;

C|

D:

Attempts:

3 left

💡 Hint

Common Mistakes

Using comma when the file uses semicolons

Using pipe or colon which are different delimiters

The sep parameter defines the delimiter used in the CSV file. For semicolon-separated files, use ';'.

4fill in blank

hard

Fill both blanks to read 'data.csv' using only columns 'Name' and 'Age'.

Pandas

import pandas as pd
df = pd.read_csv('data.csv', usecols=[1], dtype=[2])

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A['Name', 'Age']

B{'Name': str, 'Age': int}

C['Name', 'Salary']

D{'Name': int, 'Age': str}

Attempts:

3 left

💡 Hint

Common Mistakes

Selecting wrong columns in usecols

Mixing up data types in dtype

usecols selects columns to load. dtype sets data types for columns.

5fill in blank

hard

Fill all three blanks to read 'data.csv' skipping the first row, setting index to 'ID', and parsing dates in 'Date' column.

Pandas

import pandas as pd
df = pd.read_csv('data.csv', skiprows=[1], index_col=[2], parse_dates=[3])

Drag options to blanks, or click blank then click option'

A1

B'ID'

C['Date']

D0

Attempts:

3 left

💡 Hint

Common Mistakes

Not skipping the header row properly

Using wrong index column name

Not parsing dates correctly

skiprows=1 skips the first row, index_col='ID' sets the index column, and parse_dates=['Date'] parses the 'Date' column as dates.