Reading CSV files (read_csv) in Data Analysis Python - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the purpose of the read_csv function in data analysis?

The read_csv function is used to load data from a CSV (Comma-Separated Values) file into a DataFrame, which is a table-like structure for easy data analysis.

beginner

How do you specify a different delimiter when reading a CSV file with read_csv?

You use the delimiter or sep parameter to tell read_csv what character separates the values, for example: pd.read_csv('file.csv', delimiter=';').

beginner

What does the header=None argument do in read_csv?

It tells read_csv that the CSV file has no header row, so pandas will assign default column names as numbers starting from 0.

intermediate

How can you read only specific columns from a CSV file using read_csv?

Use the usecols parameter with a list of column names or indices you want to load, for example: pd.read_csv('file.csv', usecols=['Name', 'Age']).

beginner

What happens if the CSV file contains missing values when using read_csv?

Pandas will automatically represent missing values as NaN (Not a Number), which you can later handle or clean in your analysis.

Which function is used to load data from a CSV file into a DataFrame?

A read_csv

B load_data

C import_csv

D open_csv

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

How do you tell read_csv that the file has no header row?

A header=None

B skip_header=True

C no_header=True

D header=0

Using header=None tells pandas the CSV file has no header row.

What parameter do you use to read only certain columns from a CSV file?

A columns

B select_cols

C usecols

D cols

The usecols parameter specifies which columns to load.

If your CSV uses semicolons instead of commas, which parameter should you change?

A header=';'

B separator=','

C sep=','

D delimiter=';'

Set delimiter=';' or sep=';' to read files with semicolon separators.

What does pandas use to represent missing values when reading CSV files?

A None

B NaN

C 0

D Empty string

Pandas uses NaN to represent missing values.

Explain how to load a CSV file that uses tabs as separators and has no header row.

Think about how to tell pandas about the separator and header.

Describe how you would load only the columns 'Name' and 'Age' from a CSV file using read_csv.

Focus on selecting specific columns during loading.

Practice

1. What does the read_csv function in pandas do?

easy

A. Saves a DataFrame to a CSV file

B. Loads data from a CSV file into a DataFrame

C. Deletes a CSV file from disk

D. Creates a new empty CSV file

Solution

1. Step 1: Understand the purpose of read_csv

   The read_csv function is used to load data from a CSV file into a pandas DataFrame, which is a table-like data structure.

2. Step 2: Differentiate from other file operations

   Saving or deleting files are done by other functions, not read_csv. This function only reads and loads data.

3. Final Answer:

   Loads data from a CSV file into a DataFrame -> Option B

4. Quick Check:

   read_csv = Load CSV data [OK]

Hint: Remember: read_csv means read and load CSV data [OK]

Common Mistakes:

• Confusing read_csv with saving functions
• Thinking it creates or deletes files
• Assuming it returns raw text instead of DataFrame

2. Which of the following is the correct syntax to load a CSV file named data.csv using pandas?

easy

A. pd.read_csv('data.csv')

B. pd.load_csv('data.csv')

C. pandas.read('data.csv')

D. pd.read('data.csv')

Solution

1. Step 1: Recall pandas function for reading CSV

   The correct pandas function to read CSV files is read_csv, called as pd.read_csv() if pandas is imported as pd.

2. Step 2: Check the syntax correctness

   The argument should be the filename as a string inside parentheses. So pd.read_csv('data.csv') is correct.

3. Final Answer:

   pd.read_csv('data.csv') -> Option A

4. Quick Check:

   Correct function name and syntax = pd.read_csv('data.csv') [OK]

Hint: Use pd.read_csv('filename.csv') to load CSV files [OK]

Common Mistakes:

• Using pd.load_csv which does not exist
• Using pd.read instead of read_csv
• Forgetting quotes around filename

3. Given the CSV file sample.csv with content:

name,age
Alice,30
Bob,25
Charlie,35

What will be the output of this code?

import pandas as pd
df = pd.read_csv('sample.csv')
print(df.head(2))

medium

A. Throws an error because head() needs no arguments

B. Prints all rows because head() defaults to all

C. Prints only the column names without data

D. Prints first 2 rows with columns 'name' and 'age'

Solution

1. Step 1: Understand what read_csv does here

   The code loads the CSV file into a DataFrame with columns 'name' and 'age' and three rows.

2. Step 2: Understand head(2) output

   The head(2) function returns the first 2 rows of the DataFrame, including column headers.

3. Final Answer:

   Prints first 2 rows with columns 'name' and 'age' -> Option D

4. Quick Check:

   head(2) = first 2 rows [OK]

Hint: head(n) shows first n rows of DataFrame [OK]

Common Mistakes:

• Thinking head() shows all rows
• Assuming head() requires no arguments
• Expecting only column names without data

4. What is wrong with this code snippet?

import pandas as pd
df = pd.read_csv(data.csv)
print(df.head())

medium

A. Missing quotes around filename 'data.csv'

B. Using print instead of display

C. read_csv cannot be used without specifying separator

D. head() cannot be called without an argument

Solution

1. Step 1: Check the argument passed to read_csv

   The filename must be a string, so it needs quotes around it. Here, data.csv is not quoted, causing a NameError.

2. Step 2: Verify other parts of the code

   Using print is fine, separator defaults to comma, and head() can be called without arguments.

3. Final Answer:

   Missing quotes around filename 'data.csv' -> Option A

4. Quick Check:

   Filename must be a string in quotes [OK]

Hint: Always put filename in quotes in read_csv [OK]

Common Mistakes:

• Forgetting quotes around filename
• Thinking head() needs an argument
• Assuming separator must always be specified

5. You have a CSV file records.csv where values are separated by semicolons (;). Which code correctly loads this file into a DataFrame?

hard

A. pd.read_csv('records.csv', sep=',')

B. pd.read_csv('records.csv', delimiter=',')

C. pd.read_csv('records.csv', sep=';')

D. pd.read_csv('records.csv', sep='|')

Solution

1. Step 1: Identify the separator used in the CSV file

   The file uses semicolons (;) to separate values, so the separator must be set to ';'.

2. Step 2: Use the correct parameter in read_csv

   The parameter sep=';' tells pandas to split columns on semicolons instead of commas.

3. Final Answer:

   pd.read_csv('records.csv', sep=';') -> Option C

4. Quick Check:

   Set sep to actual delimiter used [OK]

Hint: Use sep=';' if CSV uses semicolons as separators [OK]

Common Mistakes:

• Assuming comma is always the separator
• Using wrong sep parameter
• Confusing sep and delimiter parameters