Is anyone can provide example how to create zip file from csv file using Python/Pandas package? Thank you Answer Use From the docs: compression : string, optional a string representing the compression to use in the output file, allowed values are ‘gzip’, ‘bz2’, ‘xz’, only used when the first argument is a filename See discussion of support of zip files
Tag: csv
Python CSVkit compare CSV files
I have two CSV files that look like this.. CSV 1 CSV2 Using Python and CSVkit I am trying to create an output CSV of the rows in CSV1 by comparing it to CSV2. Does anybody have an example they can point me in the direction of? Answer I would recommended to use pandas to achieve what you are looking
How to get rid of “Unnamed: 0” column in a pandas DataFrame read in from CSV file?
I have a situation wherein sometimes when I read a csv from df I get an unwanted index-like column named unnamed:0. file.csv The CSV is read with this: This is very annoying! Does anyone have an idea on how to get rid of this? Answer It’s the index column, pass pd.to_csv(…, index=False) to not write out an unnamed index column
How to add header row to a pandas DataFrame
I am reading a csv file into pandas. This csv file consists of four columns and some rows, but does not have a header row, which I want to add. I have been trying the following: But when I apply the code, I get the following Error: What exactly does the error mean? And what would be a clean way
Read in all csv files from a directory using Python
I hope this is not trivial but I am wondering the following: If I have a specific folder with n csv files, how could I iteratively read all of them, one at a time, and perform some calculations on their values? For a single file, for example, I do something like this and perform some calculations on the x array:
Not able to parse a .csv file uploaded using Flask
I am trying to upload a CSV file, work on it to produce results, and write back (download) a new CSV file containing the result. I am very new to Flask and I am not able to get a “proper” csv.reader object to iterate and work upon. Here is the code so far, The terminal output being Whereas the file
Python save arbitrarily nested list to CSV
I have a list that is composed of strings, integers, and floats, and nested lists of strings, integer, and floats. Here is an example I want each item of the list written to a line in a CSV file. So, given the above data, the file would look like this: There are lots of resources about how to write a
Convert commas decimal separators to dots within a Dataframe
I am importing a CSV file like the one below, using pandas.read_csv: Example of CSV file: The problem is that when I later on in my code try to use these values I get this error: TypeError: can’t multiply sequence by non-int of type ‘float’ The error is because the number I’m trying to use is not written with a
Sorting entire csv by frequency of occurence in one column
I have a large CSV file, which is a log of caller data. A short snippet of my file: I want to sort the entire list by the frequency of occurrence of customers so it will be like: I’ve tried groupby, but that only prints out the Company Name and the frequency but not the other columns, I also tried
Pandas read multiindexed csv with blanks
I’m struggling with properly loading a csv that has a multi lines header with blanks. The CSV looks like this: What I would like to get is: When I try to load with pd.read_csv(file, header=[0,1], sep=’,’), I end up with the following: Is there a way to get the desired result? Note: alternatively, I would accept this as a result: