Currently the code is a blanket statement that is replacing an matches it finds at all so there are multiple rows "Product" being replaced at once with the same data. How can I target each specific product set individually and replace only the Color=CHINA PEARL under the desired product, in this case it would be DETAILED ELEGANCE PATTERN. For example Color=CHINA PEARL may appear several times within the CSV. ) however the issue is there are many duplicates. I'm trying to write something in Python that will replace the data below each Product (Color. The image uploaded is of CSV1 before the script is run that will import any data. Essentially it is tasked to read CSV1 and CSV2 and combine data within certain cells. This is what the current code looks like. Writer = csv.DictWriter(file, fieldnames=fieldnames)Ĭompare_and_replace('CSV1.csv', 'CSV2.csv') With open('ImageImport.csv', 'w', newline='') as file: # Write the updated data to a new CSV file "ImageImport.csv" # Insert "Y" in row, column with the header "Product Image Is Thumbnail - 1"Ĭsv1_data = "Y" # Import data from CSV2 under the column "Description" into ImageImport.csvĬsv1_data = description # Update the Image URL in ImageImport.csv # Search in CSV2 for values in "Main Image" and import them into ImageImport.csv Updated_product_name = product_name.replace("#0057A6", image_url)ĭata = updated_product_name # Update the product name with the new image URL # Iterate over CSV2 and update CSV1 data if a match is found # Load CSV1 data into a list of dictionaries for easy lookup and preservation of orderĬsv1_data = list(reader1) # Convert reader1 to a list of dictionaries You might also like this article on dictionary comprehension in python.Def compare_and_replace(csv1_file, csv2_file): To learn more about lists, you can read this article on list comprehension in python. In this article, we have discussed how we can read a csv file into a list of dictionaries in python. The program to read a csv into list of dictionaries using the DictReader() method and a for loop is as follows. Don’t forget to close the file using the close() method at the end of the program.After execution of the for loop, we will get the entire csv file as a list of dictionaries. After that, we will we will add each dictionary from the DictReader object to the list using a for loop. To read the csv file into list of dictionaries, we will first create an empty list.In the dictionary, the keys consist of the column names of the csv file whereas the values associated with the keys are values present in a particular column in a row. The DictReader object works as an iterator and contains each row of the csv file as a dictionary.The csv.DictReader() function takes the file object as its input argument and returns a DictReader object. After obtaining the file object from the open() function, we will create a DictReader object using the csv.DictReader() function.After execution, it returns a file object that contains the csv file. The open() function takes the file name as its first input argument and the literal “r” as its second input argument to show that the file is opened in the read mode. First, we will open the csv file using the open() function in the read mode.After creating the DictReader object, we can create a list of dictionaries from the csv file using the following steps. To read a csv file into a list of dictionaries, we will create a csv.DictReader object using the csv.DictReader() method. In python, we can use the csv module to work with csv files. These elements become the keys of the resulting dictionary. The fieldnames parameter is a sequence whose elements are associated with the fields of the input data in order. Read CSV Into List of Dictionaries Using csv.DictReader() 18 Use csv.DictReader: Create an object which operates like a regular reader but maps the information read into a dict whose keys are given by the optional fieldnames parameter. In this article, we will discuss how we can read a csv file into a list of dictionaries in python. Similarly, a python dictionary is used to store key-value pairs in Python. CSV files are used to store structured data where each row in the csv file stores an entry in which each value is associated with the column name.
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