循环遍历CSV文件中的数据，以便将“ 1”和“ 0”输出到文本文件（Python）

Question

I have recently started learning Python and have run into a problem in trying to format some data for a project I am working on. I have managed to take in a CSV file as an input and I am now trying to go through that data and output '1's and '0's based upon the data, in to a text file.

I have the following code so far:

data = {} 
productIds = [] 

for row in reader:
    productIds.append(row['productCode']) 
    if row['basketID'] not in data:
        data[row['basketID']] = [row['productCode']]
    else:
        data[row['basketID']].append(row['productCode'])

productIds = sorted(set(productIds))

for item in productIds:
    txtFile.write("%s " % item)
txtFile.write('\n')

for key in data: # Will loop through each basket
    for value in data[key]: #Loop through each product in basket
        for i in productIds: # Go through list of available products
            if value == i: 
                txtFile.write('1 ')
            else:
                txtFile.write('0 ')
    txtFile.write('\n')

The result:

23 24 25 #Products 
1  0  0  0 1 0 0 0 1 #Basket 1
1  0  0              #Basket 2
1  0  0              #Basket 3
0  0  1              #Basket 4
0  1  0  0 0 1       #Basket 5

Expected result:

23 24 25 #Products
1  1  1  #Basket 1  
1  0  0  #Basket 2  
1  0  0  #Basket 3  
0  0  1  #Basket 4
0  1  1  #Basket 5

CSV File:

basketID productCode 
1        23  
1        24  
1        25  
2        23  
3        23  
4        25  
5        24  
5        25  

I believe it is going wrong when looping through the product list against the same product, but I am not sure how else to achieve this.

Answer 1

I think you should try this.First read as Dataframe

>>> df = pd.read_csv("lia.csv")
>>> df
   basketID  productCode
0         1           23
1         1           24
2         1           25
3         2           23
4         3           23
5         4           25
6         5           24
7         5           25

Then

g1 = df.groupby( [ "productCode","basketID"] ).count()
g1
Empty DataFrame
Columns: []
Index: [(23, 1), (23, 2), (23, 3), (24, 1), (24, 5), (25, 1), (25, 4), (25, 5)

Answer 2

The problem lies in the last for loop. You are traversing for each basket and iterating over each product in the current basket. For each item you are checking that if it is equal to current productId. As there are 3 productIds you are getting 3x entries of item present in basket.

Example: For basket1 , you are looping through first item=>23 for this you are making 3 entries in your output file: for i in productIds 1. 23 = 23 => 1 2. 23 = 24= >0 3. 23= 25=> 0

Additionally, you have one more problem. As your dict is not sorted by keys the order of basket looping is not guaranteed to be from basket1 to basket5 in increasing order.

Replace the last for loop with:(sorting the dict followed by the correct iteration)

data=collections.OrderedDict(sorted(data.items()));
for key in data: # Will loop through each basket
    for productId in productIds: #Loop through each productId
        if productId in data[key]: # check if productId in the basket products 
            txtFile.write('1 ')
        else:
            txtFile.write('0 ')
    txtFile.write('\n')

Output:

23 24 25 
1 1 1 
1 0 0 
1 0 0 
0 0 1 
0 1 1 

Answer 3

Try this:

data = {} 
productIds = [] 

for row in reader:
    productIds.append(row['productCode']) 
    if row['basketID'] not in data:
        data[row['basketID']] = set(row['productCode'])
    else:
        data[row['basketID']].add(row['productCode'])

productIds = sorted(set(productIds))

for item in productIds:
    txtFile.write("%s " % item)
txtFile.write('\n')

for key in data: # Will loop through each basket
    for value in sorted(data[key]): #Loop through each product in basket
        for i in productIds: # Go through list of available products
            if value == i: 
                txtFile.write('1 ')
            else:
                txtFile.write('0 ')
    txtFile.write('\n')