niffy | Perceptual diffing suite built on Nightmare | UI Testing library
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- diff from another
- Watch for differences
- Creates a new Naveryyy
- Asynchronously read a PNG file .
- Return the image path for the given image .
- Writes a PNG file .
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QUESTION
I have this backup program I am working on that uses Windows Forms for the design.
All is working well except for one button so I will spare the entire code.
I have one Button that allows the user to open a CSV
file from a certain location to edit in their default CSV editor program (i.e., Excel, Libre etc.) and the Button works fine as this:
ANSWER
Answered 2021-Jul-14 at 06:46As Jimi said, you could use Process.Start Method to open a csv file with the default editor.
First, please add namespace reference.
QUESTION
I have a column (series) of values I'm trying to move characters around and I'm going nowhere fast! I found some snippets of code to get me where I am but need a "Closer". I'm working with one column, datatype (STR). Each column strings are a series of numbers. Some are duplicated. These duplicate numbers have a (n-) in front of the number. The (n) number will change based on how many duplicate numbers strings are listed. Some may have two duplicates, some eight duplicates. Doesn't matter, order should stay the same.
I need to go down through each cell or string, pluck the (n-) from the left of string, swap the two characters around, and append it to the end of the string. No number sorting needed. The column is 4-5k lines long and will look like the example given all the way down. No other special characters or letters. Also, the duplicate rows will always be together no matter where in the column.
My problem is the code below actually works and will step through each string, evaluate it for a dash, then process the numbers in the way I need. However, I have not learned how to get the changes back into my dataframe from a python for-loop. I was really hoping that somebody had a niffy lambda fix or a pandas apply function to address the whole column at once. But I haven't found anything that I can tweak to work. I know there is a better way than slowly traversing down through a series and I would like to learn.
Two possible fixes needed:
- Is there a way to have the code below replace the old df.string value with the newly created df.string value? If so, please let me know.
- I've been trying to read up on df.apply using the split feature so I can address the whole column at once. I understand it's the smarter play. Is there a couple of lines code that would do what I need?
Please let me know what you think. I appreciate the help. Thank you for taking the time.
...ANSWER
Answered 2020-Jul-09 at 01:34You can use df.str.replace():
If we recreate your example with a file containing all your values and retain column1 as the column name:
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