用分隔符/sep 分隔 csv 列

Question

My goal is to separate data stored in cells to multiple columns in the same row.

For example, I would like to take data that looks like this:

Row 1: [<1><2>][<3><4>][][]

Row 2: [<1><2>][<3><4>][][]

Into data that looks like this:

Row 1: [1][2][3][4]

Row 2: [1][2][3][4]

I tried using the code below to pull the csv and separate each line at the ">"

df = pd.read_csv('file.csv', engine='python', sep="\*>", header=None)

However, the code did not function as anticipated. Instead, the separation occurred at seemingly random and unpredictable points (I'm sure there's a pattern but I don't see it.) And each break created another row as opposed to another column. For example:

Row 1: [<1>][<2>]

Row 2: [<3>]

Row 3: [<4>]

I thought the issue might lie with reading the CSV file so I tried just re-scraping the site with the separator included but it produced the same results so I'm assuming its an issue with the separator call. However, I found that call after trying many others that caused various errors. For example, when I tried using sep = '>' I got the following error: ParserError: '>' expected after '"' and when I tried sep = '\>' , I got the following error: ParserError: Expected 36 fields in line 1106, saw 120. Error could possibly be due to quotes being ignored when a multi-char delimiter is used.

These errors sent me looking though multiple resources including this and this among others.

However, I have find no resources that have successfully demonstrated how I can separate each column within a row following the use of a '>' delimiter. If anyone knows how to do this, please let me know. Your help is much appreciated!

Update:

Here is an actual screenshot of the CSV file for a better understanding of what I was trying to demonstrate above. My end goal is to have all the data is columns I+ have data on one descriptive factor as opposed to many as they do now.

Answer 1

Would this work:

string="[<1><2>][<3><4>][][]"
string=string.replace("[","")
string=string.replace("]","")
string=string.replace("<","[")
string=string.replace(">","]")
print(string)

Result:

[1][2][3][4]

Answer 2

I ended up using Google Sheets. Once you upload the csv there is a header titled "data" and then a sub-section titled "split text to columns."

If you want a faster way to do this with code, you can also do the following with pandas:

# new data frame with split value columns 
new = data["Name"].str.split(" ", n = 1, expand = True) 

# making separate first name column from new data frame 
data["First Name"]= new[0] 

# making separate last name column from new data frame 
data["Last Name"]= new[1] 

# Dropping old Name columns 
data.drop(columns =["Name"], inplace = True) 

# df display 
data