I have a csv file of around 42000 lines and around 80 columns, from which I need to remove leading Zero’s, hence I am using Pandas to_csv and saving it back to text file by which leading Zero’s are removed. Any column may contain null values in any row, but those columns are getting converted to Float datatype and getting
Tag: export-to-csv
How can I combine different dataframes into one csv in Python?
I have 2 dataframes with different columns. And I want to combine those into 1 csv file. Both headers should be included and there shouldn’t be empty value if columns aren’t matched. I tried to use pd.concat, but I need the result to be like below: Answer You can do this using Pandas to_csv and setting the mode parameter to
wont create a csv file [closed]
Closed. This question needs details or clarity. It is not currently accepting answers. Want to improve this question? Add details and clarify the problem by editing this post. Closed 12 months ago. Improve this question It still won’t create a all_data.csv file. Answer https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.to_csv.html According to this, 1st argument is path. From your example it will save your .csv in
Read CSV file with Python function
I’m trying to write my read/write function to a csv, but it can’t return any value. I’m reading from a CSV, replacing the ” ; ” in the second column with ” ” and performing and saving the csv already handled. But for some reason it doesn’t save my csv, is my function wrong? I’m starting out in the Python
How to get rid of the row numbers, to_csv?
after predicting the target value for the classification problem trying to get the predicted values in a .csv file along with the id of particular data instance but getting the unnecessary row numbers. x_test.head() image to.csv() image Answer You index=False , doc specifies this argument
Exporting values to existing excel file to same column
I’m running a script every day to get the date and values that I save as a data frame. Something like this: If I use the command ‘df.to_csv(“file.csv”)’ I get my data frame in an excel sheet. However, when I run the script for the following day (12/02/2021) I want to get the values for the same excel sheet. How
Grouping data in a manner to export them as a CSV file
I have a messy data which seems like I want to group them in a way that they would look like I tried mystr.split() to end up in a list and then define the following function to group them in 3’s: I was pretty sure that was going to work, however, I got the following output: I don’t know why
How to remove NaN on CSV?
I have a .csv file of a table consisting of 12 col and 30k rows. One of the col is ‘mentions’, some of the data are empty (NaN). I am trying to remove all the rows where mentions = NaN. I don’t want to fill it with new data. I just wanna remove those rows so they wont be part
Remove leading comma in header when using pandas to_csv
By default to_csv writes a CSV like But I want it to write like this: How do I achieve this? I can’t set index=False because I want to preserve the index. I just want to remove the leading comma. Answer It is possible by write only columns without index first and then data without header in append mode:
Pandas Multiindex to CSV without duplicate Index
For the life of me I can’t figure out how to remove the duplicate index items created when writing a multiindex dataframe to CSV. While there is this answer out there, it doesn’t apply to me per se because my second level has all different values. This is a chunk of the dataframe I have, it just goes on for