Replace in a CSV File Value of a Column

Replace column values from a csv file with batch

You need all the tokens (for writing the modified file), not just the second one:

for /f "tokens=1,2,* delims=," %%A in (%srcfile%) do echo %%A,testuser,%%C

(where * is "the rest of the line, undelimited"). %%B would be the username, so just write the replacement string instead.

You could use an if statement to process the first line differently, or you process it separately:

<"%srcfile%" set /p header=
(
    echo %header%
    for /f "skip=1 tokens=1,2,* delims=," %%A in (%srcfile%) do echo %%A,testuser,%%C
) > "%outfile%"

Change specific value in CSV file via Python

This is the solution opening the csv file, changing the values in memory and then writing back the changes to disk.

r = csv.reader(open('/tmp/test.csv')) # Here your csv file
lines = list(r)

Content of lines:

[['Ip', 'Sites'],
 ['127.0.0.1', '10'],
 ['127.0.0.2', '23'],
 ['127.0.0.3', '50']]

Modifying the values:

lines[2][1] = '30'

Content of lines:

[['Ip', 'Sites'],
 ['127.0.0.1', '10'],
 ['127.0.0.2', '30'],
 ['127.0.0.3', '50']]

Now we only have to write it back to a file

writer = csv.writer(open('/tmp/output.csv', 'w'))
writer.writerows(lines)

How to replace values of a columns of CSV in R shiny

You just need to add the fileUploader logic to fill my_data accordingly:

ui <- fluidPage(
   sidebarLayout(
      sidebarPanel(
         fileInput("file1", "Choose CSV File", accept = ".csv"),
         checkboxInput("header", "Header", TRUE),
         selectInput("col", "Column to search:", NULL),
         textInput("old", "Replace:"),
         textInput("new", "By:"),
         actionButton("replace", "Replace!"),
      ),
      mainPanel(
         DTOutput("table1")
      )
   )
)

server <- function(input, output, session) {
   my_data <- reactiveVal(NULL)
   
   observeEvent(input$file1, {
      file <- input$file1
      ext <- tools::file_ext(file$datapath)
      req(file)
      validate(need(ext == "csv", "Please upload a csv file"))
      my_data(read.csv(file$datapath, header = input$header))
      updateSelectInput(session, "col", choices = names(my_data()))
   })
   
   observeEvent(input$replace, {
      req(input$col)
      dat <- req(my_data())
      traf <- if (is.numeric(dat[[input$col]])) as.numeric else identity
      my_data(dat %>%
                 mutate(!!rlang::sym(input$col) := 
                           replace(!!rlang::sym(input$col),
                                   as.character(!!rlang::sym(input$col)) == input$old,
                                   input$new) %>% 
                           traf()))
   })
   
   output$table1 <- renderDT(
      req(my_data())
   )
}

Replace csv file first column with list values in python

Just use loc to modify the one column of your dataframe:

example = pd.DataFrame({0: [1, 2, 3],
                        2: ["a", "b", "c"]})

replacement_list = ["ab", "cd", "ef"]
example.loc[:, 2] = replacement_list
print(example)

   0   2
0  1  ab
1  2  cd
2  3  ef

I encourage you to look at the doc about the behaviour of loc and about indexing/selecting part of your dataframe.
Of course, it will work as intended if your list has the same size of the number of rows of the dataframe. If not, you can convert your list into a series first to handle the missing data.

How to replace value of a column converted to day and month to a text using Python?

You can use pandas.to_datetime :

new["Room"]= (
                pd.to_datetime(new["Room"], format="%d-%b", errors="coerce")
                    .dt.strftime("%#m-%#d")
                    .fillna(new["Room"])
                )

Example :

     col
0  1-Feb
1  2-Feb
2  3-Mar
3    2-1

Gives :

   col
0  2-1
1  2-2
2  3-3
3  2-1

NB: In case you're facing errors, you need to give a minimal reproducible example to show how look like your original (.csv) opened in a text editor and not in Excel.

Replace 'space' in certain value of csv columns

Select 'Attachment' columns using filter and replace all whitespaces by '%20' then update your dataframe in place:

df.update(df.filter(like='Attachment').replace(' ', '%20', regex=True))

My advise if you need to escape HTML entities is to use quote from urllib module:

from urllib.parse import quote

df.update(df.filter(like='Attachment').fillna('').applymap(quote))

Update

Try:

out = df.filter(like='Attachment').unstack().str.split(';').explode()
out = out.where(~(out.str.startswith('file://').fillna(False)), 
                out.str.replace(' ', '%20'))
df.update(out.dropna().groupby(level=[0, 1]).apply(';'.join).unstack(0))

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