I am in the process of learning ColdFusion and I am trying to work with spreadsheets using spreadsheetFormatRows(spreadsheetObject, dataFormat, rangeOfRowsFormated)
How can I set the range to include all of the rows, except the header row, which is for column name? Is there a function that returns the number of the rows on cfspreadsheet object, so I can set the range to '2-rowCount'?
I tried spreadsheetFormatRows(theSheet, headerFormat, 2-50); and works fine and formats rows 2 to 50, but I don't want to have that hard-coded.
Thank you in advance.
The spreadsheet object has an attribute rowcount. You can do spreadsheetFormatRows(theSheet, format, "2-#theSheet.rowCount#");
<cfscript>
mySheet = spreadSheetNew("My Sheet");
spreadSheetAddRow(mySheet, "'Col. A','Col. B','Col. C'");
for(i=1; i <= RandRange(1, 100); i++){
spreadSheetAddRow(mySheet, "'Row A#i#','Row B#i#','Row C#i#'");
}
spreadSheetFormatRow(mySheet, {bold = true, fontsize = 24}, 1);
spreadSheetFormatRows(mySheet, {fontsize = 16}, "2-#mySheet.rowcount#");
cfheader(name = "Content-Disposition", value = 'inline; fileName="test.xls"');
cfcontent(type="application/vnd.ms-excel", variable="#spreadSheetReadBinary(mySheet)#");
</cfscript>
Try Online
Keep track of the number of rows as you populate them and save the value to a variable. Simpler yet, if they are query results, use the recordcount variable from cfquery.
Remember to add 1 so you format the last row.
Related
I have a following data table:
I need to create a column called FINAL VALUE with certain rules in the power query editor:
The FINAL VALUE is created based on the COUNTRY
If VALUE is greater than 100, then the previous value will be taken
if the previous values (no previous value such as 202001) are all greater than 100, then 100
So the final table should look like:
I sort COUNTRY and DATE, and then I try to apply loop in M Query. As I am not familiar with the function in M query, I have hard time figuring out. I appreciate any help. Thank you.
I believe you are better of in DAX. You can create a new column like below:
Final Value =
var curCountry = TableCountry[Country]
var curDate = TableCountry[Date]
var prevDate = CALCULATE(MAX(TableCountry[Date]), FILTER(TableCountry, curDate >= TableCountry[Date] && curCountry = TableCountry[Country] && TableCountry[Value] <=100))
return LOOKUPVALUE(TableCountry[Value], TableCountry[Country], curCountry, TableCountry[Date], prevDate, 100)
I am looping through an excel sheet, looking for a specific name. When found, I print the position of the cell and the value.
I would like to find the position and value of a neighbouring cell, however I can't get .cell() to work by adding 2, indicating I would like the cell 2 columns away in the same row.
row= row works, but column= column gives error, and column + 2 gives error. Maybe this is due to me listing columns as 'ABCDEFGHIJ' earlier in my code? (For full code, see below)
print 'Cell position {} has value {}'.format(cell_name, currentSheet[cell_name].value)
print 'Cell position next door TEST {}'.format(currentSheet.cell(row=row, column=column +2))
Full code:
file = openpyxl.load_workbook('test6.xlsx', read_only = True)
allSheetNames = file.sheetnames
#print("All sheet names {}" .format(file.sheetnames))
for sheet in allSheetNames:
print('Current sheet name is {}'.format(sheet))
currentSheet = file[sheet]
for row in range(1, currentSheet.max_row + 1):
#print row
for column in 'ABCDEFGHIJ':
cell_name = '{}{}'.format(column,row)
if currentSheet[cell_name].value == 'sign_name':
print 'Cell position {} has value {}'.format(cell_name, currentSheet[cell_name].value)
print 'Cell position TEST {}'.format(currentSheet.cell(row=row, column=column +2))
I get this output:
Current sheet name is Sheet1
Current sheet name is Sheet2
Cell position D5 has value sign_name
and:
TypeError: cannot concatenate 'str' and 'int' objects
I get the same error if I try "column = column" as "column = column +2".
Why does row=row work, but column=column dosen't? And how to find the cell name of the cell to the right of my resulting D5 cell?
The reason row=row works and column=column doesn't is because your column value is a string (letter from A to J) while the column argument of a cell is expecting an int (A would be 1, B would be 2, Z would be 26, etc.)
There are a few changes I would make in order to more effectively iterate through the cells and find a neighbor. Firstly, OpenPyXl offers sheet.iter_rows(), which given no arguments, will provide a generator of all rows that are used in the sheet. So you can iterate with
for row in currentSheet.iter_rows():
for cell in row:
because each row is a generator of cells in that row.
Then in this new nested for loop, you can get the current column index with cell.column (D would give 4) and the cell to the right (increment by one column) would be currentSheet.cell(row=row, column=cell.column+1)
Note the difference between the two cell's: currentSheet.cell() is a request for a specific cell while cell.column+1 is the column index of the current cell incremented by 1.
Relevant OpenPyXl documentation:
https://openpyxl.readthedocs.io/en/stable/api/openpyxl.cell.cell.html
https://openpyxl.readthedocs.io/en/stable/api/openpyxl.worksheet.worksheet.html
I need some help with Google Sheets.
I have two columns, let's say A1-A100 and C1-C100. In A1-A100 I have a list of names (students), but there may be less than 100, so it could be blank from A85 to A100 for example. In C1-C100 I have grades, from 0 to 10. I need a script that auto-fills blank cells in grades (C) column with "AUS" (short for 'not present' in Spanish). But only cells corresponding to some student... so from C85 to C100, it should be left blank.
Any help would be appreciated.
Using the functions and classes from the Spreadsheet service [1], i made and tested the code for what you want to do:
function fill() {
var tss = SpreadsheetApp.getActiveSpreadsheet();
var values = tss.getRange("Sheet1!B1:B100").getValues();
for(i=0; i<values.length; i++) {
var value = values[i][0];
if (value == "") {
var rangeB = tss.getSheetByName("Sheet1").getRange(i+1,2);
var rangeA = tss.getSheetByName("Sheet1").getRange(i+1,1);
if(!rangeA.isBlank()) {
rangeB.setValue("AUS");
}
}
}
}
That function needs to be inside a script bound to the Spreadsheet, then you can add a macro [2] so you can run the function from the Sheets UI.
[1] https://developers.google.com/apps-script/reference/spreadsheet/
[2] https://developers.google.com/apps-script/guides/sheets/macros
=ARRAYFORMULA(IF((A2:A<>"")*(B2:B=""), "AUS", B2:B))
How can I sum fields on each row in a tabular form in APEX 4.2 to get a total for that row before I submit the page in order to do page validation?
For example if the first row has 6 in field a and 6 in field b the total for the first row should be 12 and on the second row if field b is 5 and field c is 5 the total for the second row should be 10.
So I want to get totals based on rows not column. Is that possible?
Yes, its possible. If you know javascript/jquery, you'll get along well with my solution. This is what you have to do:
get the name attribute(using inspect element of your browser) of the field you want to sum up. Names of fields in oracle apex usually goes like 'f01' or 'f02' and so on. Once you get the fields, create a javascript function or you can use this one if you like:
function sumUpRows(columnforsum,itemstobeadded){
var numofcols = arguments.length;
var numofrows = $("[name=" + arguments[0] + "]").length;
var summ = 0;
for(x=0;x<numofrows;x++){
for(i=1;i<numofcols;i++){
summ = summ + Number($("[name=" + arguments[i] + "]").eq(x).val());
}
$("[name=" + columnforsum + "]").eq(x).val(summ);
}
}
Put function above in "function and global variable declaration" part of your page. Then create a "before page submit" dynamic action. Set its action to "execute javascript" then put this line of code:
sumUpRows("nameoffieldwheresumwillbeassigned","nameofitem1","nameofitem2","nameofitem3");
Here's a sample :
sumUpRows("f04","f01","f02","f03");
For your question in the comment section, the answer is yes. To get the sum of a row automatically as you fill up the boxes on that row, you can use this function:
function sumUpRowsAsYouGo(whatelement){
var numofrows=$("[name=f01]").length;
var summ = 0;
for(i=0;i<numofrows;i++){
if($(whatelement).attr("id") == $("[name=" + $(whatelement).attr("name") + "]").eq(i).attr("id")){
for(a=1;a<(arguments.length-1);a++){
summ += Number($("[name="+ arguments[a] + "]").eq(i).val());
}
$("[name="+ arguments[arguments.length-1] + "]").eq(i).val(summ);
break;
}
}
}
you can use this function like this(put these lines in the "Execute on Page load" and "after refresh" dynamic action of your tabular form region):
$("[name=f01]").change(function(){
sumUpRowsAsYouGo(this,"f01","f02","f03","f04");
}
);
$("[name=f02]").change(function(){
sumUpRowsAsYouGo(this,"f01","f02","f03","f04");
}
);
$("[name=f03]").change(function(){
sumUpRowsAsYouGo(this,"f01","f02","f03","f04");
}
);
I have time series data in two separate DataFrame columns which refer to the same parameter but are of differing lengths.
On dates where data only exist in one column, I'd like this value to be placed in my new column. On dates where there are entries for both columns, I'd like to have the mean value. (I'd like to join using the index, which is a datetime value)
Could somebody suggest a way that I could combine my two columns? Thanks.
Edit2: I written some code which should merge the data from both of my column, but I get a KeyError when I try to set the new values using my index generated from rows where my first df has values but my second df doesn't. Here's the code:
def merge_func(df):
null_index = df[(df['DOC_mg/L'].isnull() == False) & (df['TOC_mg/L'].isnull() == True)].index
df['TOC_mg/L'][null_index] = df[null_index]['DOC_mg/L']
notnull_index = df[(df['DOC_mg/L'].isnull() == True) & (df['TOC_mg/L'].isnull() == False)].index
df['DOC_mg/L'][notnull_index] = df[notnull_index]['TOC_mg/L']
df.insert(len(df.columns), 'Mean_mg/L', 0.0)
df['Mean_mg/L'] = (df['DOC_mg/L'] + df['TOC_mg/L']) / 2
return df
merge_func(sve)
And here's the error:
KeyError: "['2004-01-14T01:00:00.000000000+0100' '2004-03-04T01:00:00.000000000+0100'\n '2004-03-30T02:00:00.000000000+0200' '2004-04-12T02:00:00.000000000+0200'\n '2004-04-15T02:00:00.000000000+0200' '2004-04-17T02:00:00.000000000+0200'\n '2004-04-19T02:00:00.000000000+0200' '2004-04-20T02:00:00.000000000+0200'\n '2004-04-22T02:00:00.000000000+0200' '2004-04-26T02:00:00.000000000+0200'\n '2004-04-28T02:00:00.000000000+0200' '2004-04-30T02:00:00.000000000+0200'\n '2004-05-05T02:00:00.000000000+0200' '2004-05-07T02:00:00.000000000+0200'\n '2004-05-10T02:00:00.000000000+0200' '2004-05-13T02:00:00.000000000+0200'\n '2004-05-17T02:00:00.000000000+0200' '2004-05-20T02:00:00.000000000+0200'\n '2004-05-24T02:00:00.000000000+0200' '2004-05-28T02:00:00.000000000+0200'\n '2004-06-04T02:00:00.000000000+0200' '2004-06-10T02:00:00.000000000+0200'\n '2004-08-27T02:00:00.000000000+0200' '2004-10-06T02:00:00.000000000+0200'\n '2004-11-02T01:00:00.000000000+0100' '2004-12-08T01:00:00.000000000+0100'\n '2011-02-21T01:00:00.000000000+0100' '2011-03-21T01:00:00.000000000+0100'\n '2011-04-04T02:00:00.000000000+0200' '2011-04-11T02:00:00.000000000+0200'\n '2011-04-14T02:00:00.000000000+0200' '2011-04-18T02:00:00.000000000+0200'\n '2011-04-21T02:00:00.000000000+0200' '2011-04-25T02:00:00.000000000+0200'\n '2011-05-02T02:00:00.000000000+0200' '2011-05-09T02:00:00.000000000+0200'\n '2011-05-23T02:00:00.000000000+0200' '2011-06-07T02:00:00.000000000+0200'\n '2011-06-21T02:00:00.000000000+0200' '2011-07-04T02:00:00.000000000+0200'\n '2011-07-18T02:00:00.000000000+0200' '2011-08-31T02:00:00.000000000+0200'\n '2011-09-13T02:00:00.000000000+0200' '2011-09-28T02:00:00.000000000+0200'\n '2011-10-10T02:00:00.000000000+0200' '2011-10-25T02:00:00.000000000+0200'\n '2011-11-08T01:00:00.000000000+0100' '2011-11-28T01:00:00.000000000+0100'\n '2011-12-20T01:00:00.000000000+0100' '2012-01-19T01:00:00.000000000+0100'\n '2012-02-14T01:00:00.000000000+0100' '2012-03-13T01:00:00.000000000+0100'\n '2012-03-27T02:00:00.000000000+0200' '2012-04-02T02:00:00.000000000+0200'\n '2012-04-10T02:00:00.000000000+0200' '2012-04-17T02:00:00.000000000+0200'\n '2012-04-26T02:00:00.000000000+0200' '2012-04-30T02:00:00.000000000+0200'\n '2012-05-03T02:00:00.000000000+0200' '2012-05-07T02:00:00.000000000+0200'\n '2012-05-10T02:00:00.000000000+0200' '2012-05-14T02:00:00.000000000+0200'\n '2012-05-22T02:00:00.000000000+0200' '2012-06-05T02:00:00.000000000+0200'\n '2012-06-19T02:00:00.000000000+0200' '2012-07-03T02:00:00.000000000+0200'\n '2012-07-17T02:00:00.000000000+0200' '2012-07-31T02:00:00.000000000+0200'\n '2012-08-14T02:00:00.000000000+0200' '2012-08-28T02:00:00.000000000+0200'\n '2012-09-11T02:00:00.000000000+0200' '2012-09-25T02:00:00.000000000+0200'\n '2012-10-10T02:00:00.000000000+0200' '2012-10-24T02:00:00.000000000+0200'\n '2012-11-21T01:00:00.000000000+0100' '2012-12-18T01:00:00.000000000+0100'] not in index"
You are close, but you actually don't need to iterate over the rows when using the isnull() functions. by default
df[(df['DOC_mg/L'].isnull() == False) & (df['TOC_mg/L'].isnull() == True)].index
Will return just the index of the rows where DOC_mg/L is not null and TOC_mg/L is null.
Now you can do something like this to set the values for TOC_mg/L:
null_index = df[(df['DOC_mg/L'].isnull() == False) & \
(df['TOC_mg/L'].isnull() == True)].index
df['TOC_mg/L'][null_index] = df['DOC_mg/L'][null_index] # EDIT To switch the index position.
This will use the index of the rows where TOC_mg/L is null and DOC_mg/L is not null, and set the values for TOC_mg/L to the those found in DOC_mg/L in the same rows.
Note: This is not the accepted way for setting values using an index, but it is how I've been doing it for some time. Just make sure that when setting values, the left side of the equation is df['col_name'][index]. If col_name and index are switched you will set the values to a copy which is never set back to the original.
Now to set the mean, you can create a new column, we'll call this Mean_mg/L and set the value = 0.0. Then set this new column to the mean of both columns:
# Insert a new col at the end of the dataframe columns name 'Mean_mg/L'
# with default value 0.0
df.insert(len(df.columns), 'Mean_mg/L', 0.0)
# Set this columns value to the average of DOC_mg/L and TOC_mg/L
df['Mean_mg/L'] = (df['DOC_mg/L'] + df['TOC_mg/L']) / 2
In the columns where we filled null values with the corresponding column value, the average will be the same as the values.