Problem Formulation
Given a CSV file (e.g., stored in the file with name 'my_file.csv'
).
INPUT: file 'my_file.csv'
9,8,7 6,5,4 3,2,1
Challenge: How to convert it to a list of lists (=nested list), i.e., putting the row values into the inner lists?
OUTPUT: Python list of lists
[[9, 8, 7], [6, 5, 4], [3, 2, 1]]
Method 1: csv.reader()
Method 1: csv.reader()
To convert a CSV file 'my_file.csv'
into a list of lists in Python, use the csv.reader(file_obj)
method to create a CSV file reader. Then convert the resulting object to a list using the list()
constructor.
Here’s a simple example that converts our CSV file to a nested list using this approach:
import csv csv_filename = 'my_file.csv' with open(csv_filename) as f: reader = csv.reader(f) lst = list(reader)
Output:
print(lst) # [['9', '8', '7'], ['6', '5', '4'], ['3', '2', '1']]
Method 2: One-Liner
Method 2: One-Liner
You can also convert a CSV to a list of lists using the following Python one-liner that opens the file using open()
, passes the file object into the csv.reader()
function, and convert the CSV reader object to a list using the list()
built-in function in Python.
Here’s how that looks:
import csv; lst=list(csv.reader(open('my_file.csv'))); print(lst)
Concise, isn’t it? π
The output is the same:
[['9', '8', '7'], ['6', '5', '4'], ['3', '2', '1']]
By the way: Do you need all inner elements converted to a certain data type such as integer?
If so, use the following approach on top of the nested list of strings, lst
, obtained from the previous methods:
new_lst = [[int(x) for x in inner] for inner in lst]
The converted new_lst
now contains a nested list of ints:
print(new_lst) # [[9, 8, 7], [6, 5, 4], [3, 2, 1]]
Method 3: Pandas
Method 3: Pandas
You can convert a CSV to a list of lists with Pandas by first reading the CSV without header line using pd.read_csv('my_file.csv', header=None)
function and second converting the resulting DataFrame to a nested list using df.values.tolist()
.
Here’s an example that converts the CSV to a Pandas DataFrame and then to a nested raw Python list:
import pandas as pd df = pd.read_csv('my_file.csv', header=None) lst = df.values.tolist() print(lst) # [[9, 8, 7], [6, 5, 4], [3, 2, 1]]
This was easy, wasn’t it? π
Of course, you can also one-linerize it by chaining commands like so:
lst = pd.read_csv('my_file.csv', header=None).values.tolist()
Method 4: Raw Python No Dependency
Method 4: Raw Python No Dependency
If you’re like me, you try to avoid using dependencies if they are not needed. Raw Python is often more efficient and simple enough anyways. Also, you don’t open yourself up against unnecessary risks and complexities.
Question: So, is there a simple way to read a CSV to a list of lists in raw Python without external dependencies?
Sure!
To read a CSV to a nested list in pure Python, open the file using open('my_file.csv')
, read all lines into a variable using f.readlines()
. Now, iterate over all lines, strip them from whitespace using strip()
, and split them on the delimiter ','
using split(',')
.
You can accomplish this in a simple list comprehension statement like so:
csv_filename = 'my_file.csv' with open(csv_filename) as f: lines = f.readlines() lst = [line.strip().split(',') for line in lines] print(lst)
Feel free to check out my detailed video in case you need a refresher on the powerful Python concept list comprehension:
π Related Tutorial: Understanding List Comprehension in Python.
More Python CSV Conversions
π Learn More: I have compiled an “ultimate guide” on the Finxter blog that shows you the best method, respectively, to convert a CSV file to JSON, Excel, dictionary, Parquet, list, list of lists, list of tuples, text file, DataFrame, XML, NumPy array, and list of dictionaries.
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