Python: How to Turn CSV Data in to Array

Convert from CSV to array in Python

You should use the csv module:

import csv

results = []
with open("input.csv") as csvfile:
    reader = csv.reader(csvfile, quoting=csv.QUOTE_NONNUMERIC) # change contents to floats
    for row in reader: # each row is a list
        results.append(row)

This gives:

[[0.000264, 0.000352, 8.7e-05, 0.000549], 
[0.00016, 0.000223, 1.1e-05, 0.000142], 
[0.008853, 0.006519, 0.002043, 0.009819], 
[0.002076, 0.001686, 0.000959, 0.003107], 
[0.000599, 0.000133, 0.000113, 0.000466], 
[0.002264, 0.001927, 0.00079, 0.003815], 
[0.002761, 0.00288, 0.001261, 0.006851], 
[0.000723, 0.000617, 0.000794, 0.002189]]

Python: how to turn csv data in to array

Read the file and get the items as list from it:

import csv

results = []

with open('some_array.csv','r') as f:
    lines = csv.reader(f)
    for line in lines:
        results.append([[int(i)] for i in line])

>>results
[[['11'], ['10'], ['8'], ['12'], ['13'], ['11']],
 [['0'], ['1'], ['0'], ['2'], ['3'], ['0']],
 [['5'], ['15'], ['13'], ['11'], ['18'], ['18']]]

Convert CSV to Array - Python

Maybe this is how it should be?

myList = []
import csv
with open(csvFileName) as csv_file:
    csv_reader = csv.reader(csv_file, delimiter=',')
    for row in csv_reader:
        myList.append(row)
    csv_file.close()

print(myList[0])
print(myList[0][1])

Converting CSV into Array in Python

You can do this:

with open("Solutions10.csv") as csvfile:
    result = [eval(k) for k in csvfile.readlines()]

Edit: Karl is cranky and wants you todo this:

with open("Solutions10.csv") as csvfile:
    result = []
    for line in csvfile.readlines():
        line = line.replace("[","").replace("]","")
        result.append([int(k) for k in line.split(",")]

But you're the programmer so you can do what you want. If you trust your input file eval is fine.

How to convert columns from a csv file into arrays in python with the first value being the array variable name?

If you have a large number of samples in csv file and don't want to construct DataFrame object, you can use csv module and constract your lists in an iterable way without loading whole data in memory:

import csv

csv_file = 'sample.csv'

names = []
description = []
price = []

with open(csv_file, 'r') as f:
    reader = csv.DictReader(f)
    for row in reader:
        names.append(row.get('name'))
        description.append(row.get('description'))
        price.append(row.get('price'))

print(names)
## ['Apples', 'White Bread', 'Wholemeal Bread']

print(description)
## ['A bag of 3 apples', 'A loaf of white bread', 'A loag of wholemeal bread']

print(price)
## ['1.75', '1.90', '1.45']

How to import a csv-file into a data array?

Assuming the CSV file is delimited with commas, the simplest way using the csv module in Python 3 would probably be:

import csv

with open('testfile.csv', newline='') as csvfile:
    data = list(csv.reader(csvfile))

print(data)

You can specify other delimiters, such as tab characters, by specifying them when creating the csv.reader:

    data = list(csv.reader(csvfile, delimiter='\t'))

For Python 2, use open('testfile.csv', 'rb') to open the file.

I want to convert .csv file to a Numpy array

For this, you first create a list of CSV files (file_names) that you want to append. Then you can export this into a single CSV file by reshaping Numpy-Array. This will help you to move forward:

import pandas as pd
import numpy as np

combined_csv_files = pd.concat( [ pd.read_csv(f) for f in file_names ])

Now, if you want to Export these files into Single .csv-File, use like:

combined_csv_files.to_csv( "combined_csv.csv", index=False)

Now, in order to obtain Numpy Array, you can move forward like this:

data_set = pd.read_csv('combined_csv.csv', header=None)
data_frames = pd.DataFrame(data_set)

required_array = np.array(data_frames.values)
print(required_array)

Here you can also reshape Numpy Array by using:

required_array.shape = (100, 14, 79)

I have perform simple test on cmd to confirm this:

>>> y = np.zeros((2, 3, 4))
>>> y.shape
(2, 3, 4)
>>> y.shape = (3, 8)
>>> y
array([[ 0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.],
       [ 0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.],
       [ 0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.]])

How to read strings from a csv file and convert it into a integer array?

Using a dict for a lookup and list comprehension

Ex:

check = {'low': 1, "high": 3}

with open('sample.csv') as infile:
    csv_file = csv.reader(infile)
    next(csv_file) # skip header
    result = [[check[c] for c in row] for row in csv_file]

How do I read CSV data into a record array in NumPy?

Use numpy.genfromtxt() by setting the delimiter kwarg to a comma:

from numpy import genfromtxt
my_data = genfromtxt('my_file.csv', delimiter=',')

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