Python: csv file and dictionary without Pandas

Question

I am trying to solve a simple problem...I have a file called data.csv with the following data:

enroll_code,student_id
10030,55000
10030,55804
10250,55804
10510,55000

What I am trying to do is to load the file, read the contents, and get the count of the number of values for each enroll_code. Without using Pandas, how can this be done? Here's what I have tried so far...

file = open('data.csv')
csv_reader = csv.reader(file)
next(csv_reader)
for key, value in csv_reader.items():
    print(key, len([item for item in csv_reader if item]))

Why are you doing csv_reader.items()?

juanpa.arrivillaga
– juanpa.arrivillaga

2021-02-28 02:53:32 +00:00
Commented Feb 28, 2021 at 2:53 — juanpa.arrivillaga
– juanpa.arrivillaga, Commented Feb 28, 2021 at 2:53
just curious by why don't you want to use pandas?

KillerToilet
– KillerToilet

2021-02-28 02:53:33 +00:00
Commented Feb 28, 2021 at 2:53 — KillerToilet
– KillerToilet, Commented Feb 28, 2021 at 2:53
@KillerToilet more than one way to skin a cat...

Richard Broyles
– Richard Broyles

2021-02-28 02:56:52 +00:00
Commented Feb 28, 2021 at 2:56 — Richard Broyles
– Richard Broyles, Commented Feb 28, 2021 at 2:56

Afiz · Accepted Answer · 2021-02-28 03:19:06Z

1

I think you have issues in reading the CSV file correctly. Here is the snippet for reading CSV.

    In [8]: import csv
   ...: with open("data.csv", 'r') as file:
   ...:     csv_file = csv.DictReader(file)
   ...:     count = {}
   ...:     for row in csv_file:
   ...:         entry = dict(row)
   ...:         if entry['enroll_code'] in count:
   ...:             count[entry['enroll_code']] +=1
   ...:         else:
   ...:             count[entry['enroll_code']] = 1
   ...:     print(count)
   ...:
   ...:
   ...:
{'10030': 2, '10250': 1, '10510': 1}

Inside the for loop add your logic for counting all enrollments, which you can do it using a dictionary. All the best.

edited Feb 28, 2021 at 3:19

answered Feb 28, 2021 at 3:11

Afiz

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3 Comments

Frank Over a year ago

I don't know why, seems like he wanna try it without using any data science library.

Afiz Over a year ago

@Frank for simple CSV file operation, developers don't want to use data science library. Even I would prefer the CSV library instead of NumPy, pandas if it is an operation like this.

Frank Over a year ago

Yes. I am using pandas in my project actually. I am just confused by this problem setting. :d

Frank · Accepted Answer · 2021-02-28 03:15:42Z

0

Without using Pandas. How can this be done?

Say you are read the .csv like

0,1,1,2,3,

Short Answer

Numpy.

tmp = np.loadtxt(path, dtype=np.str, delimiter=",")

To get the length of the data. Just print the shape of tmp.

print(tmp.shape)

To make it without using any libs.

def csv_reader(datafile):
    data = []
    with open(datafile, "r") as f:
        header = f.readline().split(",")  # 获取表头
        counter = 0
        for line in f:
            data.append(line) # you can split the line later.
            fields = line.split(",")
            print("line: ",line, " ", fields)
            counter += 1

    return data

if __name__ == '__main__':
    csv_reader("0.csv")

edited Feb 28, 2021 at 3:15

answered Feb 28, 2021 at 2:57

Frank

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4 Comments

Richard Broyles Over a year ago

let's try it without using any data science library...

Frank Over a year ago

@RichardBroyles Updated. Check it out.

Richard Broyles Over a year ago

wasn't what I had hoped for...here's the output... line: 10030,55000 ['10030', '55000\n'] line: 10030,55804 ['10030', '55804\n'] line: 10250,55804 ['10250', '55804\n'] line: 10510,55000 ['10510', '55000\n'] Looking for something like this.... 10030: 2 10250: 1 10510: 1

Frank Over a year ago

@RichardBroyles hi, I am posting the idea here. you need to modify the parser according to the data format in your csv file.

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