


Why Am I Getting 'TypeError: list indices must be integers or slices, not str' When Merging Lists in Python?
Handling 'TypeError: list indices must be integers or slices, not str' in Python While Merging Lists
In Python, attempting to access a list element using a string index often results in the 'TypeError: list indices must be integers or slices, not str' error. This error typically occurs when merging two lists into a single array.
To avoid this error, it is crucial to ensure that the index used to access list elements is an integer. Below are the specific issues in the provided Python code and the correct way to address them:
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Converting array_length to an Integer: In the original code, array_length is assigned the string representation of the length of array_dates. Instead, it should be the integer length value, which can be obtained using len(array_dates).
array_length = str(len(array_dates)) # Convert to: array_length = len(array_dates)
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Using range() for Loop: The for loop iterates through the indices of result_array. However, the loop definition uses array_length as the iterable, which is a string. Instead, use range(array_length) to iterate through integers.
for i in array_length: # Convert to: for i in range(array_length):
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Automatic Index Increment: In the original code, i is incremented manually after each iteration. This is unnecessary as the for loop will automatically increment the index variable.
i += 1 # Remove this line
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Alternative Approach Using zip():
Alternatively, to merge two lists of equal length, one can use the zip() function, which takes the corresponding elements from each list and creates a new list of tuples. This approach is often more concise and avoids the need for manual indexing.
dates = ['2020-01-01', '2020-01-02', '2020-01-03'] urls = ['www.abc.com', 'www.cnn.com', 'www.nbc.com'] csv_file_path = '/path/to/filename.csv' with open(csv_file_path, 'w') as fout: csv_writer = csv.writer(fout, delimiter=';', lineterminator='\n') result_array = zip(dates, urls) csv_writer.writerows(result_array)
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