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Can a CSV file have a variable number of columns?
Some CSV files don’t conform to RFC4180 and have a different number of columns on each row. For example, the following file doesn’t always have a birthDate column. If you are unfortunate enough to have a CSV file with a variable number of columns, you’ll have to use CsvListReader, as it’s the only reader that supports it.
How to match columns from CSV files [ solved ]?
I am trying to update a csv file with another csv file that shares a column. the color column is subject to change but the place column can’t. Is there an easy way to match the info from key.csv and import-file.csv? I’m kinda stuck before I can even begin. Please help! I haven’t tested any of this but it should behave as expected.
How to split a CSV file into columns?
Where that file isn’t yet opened, then create it and write the header, then always write all rows to the corresponding file, eg:
Is there a way to import CSV files?
Import-CSV is returning an array of objects which makes it much easier to use… so on the forefront, my apologies there. Now, as for your question.
Can you create a variable from a CSV file in Python?
Your CSV file contains literally the string “jan1,A”. Now, it is possible in Python to manipulate variables directly via their name, because everything is (pretty much) dictionaries all the way down. However, be aware that you’re venturing into a weird, unmaintainable and downright mad path.
How do I get column names in CSV?
Supplying a list of columns names in the read_csv () should do the trick. You can dynamically generate column names as simple counters (0, 1, 2, etc). Missing values will be assigned to the columns which your CSV lines don’t have a value for. Polished version of P.S. answer is as follows. It works.
How to handle variable number of columns with?
What you could probably do is read the file line by line, and concatenate each reading to a DataFrame: It works but not in the most elegant way, I guess… Ok. Not sure how efficient this is – but here is what I have done. Would love to hear if there is a better way to do this.