multiple-columns

问题 How can I edit my code in Vim by displaying it in any number of columns? My laptop and desktop monitors are widescreen (I suspect that is true of most monitors made in the last 5 or 10 years!). When I open any editor in full screen, more than half the screen is completely empty. I'd like to be able to effectively use the rest of the screen by splitting it into two or three columns so I can see all much more of my code in a single screen. Frankly, I'm surprised that other than Microsoft Word,

问题 Closed. This question does not meet Stack Overflow guidelines. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed 6 years ago . Improve this question I need to insert range of values into my database table. User will select a range .... e.g:20 to 100 ... So the numbers ranging from 20 to 100 must be added into the table in separate rows....How can i implement this using php script 回答1: $startIndex = 20;

问题 I have a table with two columns that contain ID's. I want to query the table to show one list of each ID from the two columns. TABLE A | B ----- 1 | 2 2 | 3 5 | 4 6 | 2 I want the result to be: TABLE A - 1 2 3 5 4 6 回答1: Use the UNION operator SELECT A FROM TABLE UNION SELECT B FROM TABLE 来源： https://stackoverflow.com/questions/22976395/mysql-get-all-unique-values-between-two-columns

问题 I have a table with two columns. One has some property names and the other has descriptions, including pre tags. I need the pre tags to not wrap and instead scroll to see overflow. I also need the first column to be sized based on the largest property name. I can't get the two to play nicely with each other. For example I can get the first column to size based on the content but the pre won't scroll: .main-content { max-width: 800px; border: 1px solid red; } pre { overflow: auto; } <div class

问题 I would like to sum the frequencies over multiple columns with pandas. The amount of columns can vary between 2-15 columns. Here is an example of just 3 columns: code1 code2 code3 27 5 56 534 27 78 27 312 55 89 312 27 And I would like to have the following result: code frequency 5 1 27 4 55 1 56 2 78 1 312 2 534 1 To count values inside one column is not the problem, just need a sum of all frequencies in a dataframe a value can appear, no matter the amount of columns. 回答1: You could stack and

问题 I want to proportionally change the column width of all columns in a QTableView widget, so that each column has the same width regardless of the data. For example, if a table has three columns, each column should always have a width of one third of the available horizontal space - and the width should be automatically updated whenever the dialog is resized by the user. So far I've only managed to resize columns to their contents, which is not what I want. Here's the code I've got so far: main

问题 I am summing across multiple columns, some that have NA. I am using dplyr::mutate and then writing out the arithmetic sum of the columns to get the sum. But the columns have NA and I would like to treat them as zero. I was able to get it to work with rowSums (see below), but now using mutate. Using mutate allows to make it more readable, but can also allow me to subtract columns. The example is below. require(dplyr) data(iris) iris <- tbl_df(iris) iris[2,3] <- NA iris <- mutate(iris, sum =

问题 I would like to perform the following operation in a pandas or pyspark dataframe but i still havent found a solution. I want to subtract the values from consecutive columns in a dataframe. The operation I am describing can be seen in the image below. Bear in mind that the output dataframe wont have any values on first column as the first column in the input table cannot be subtracted by its previous one as it doesn't exist. 回答1: diff has an axis param so you can just do this in one step: In

问题 I would like to perform the following operation in a pandas or pyspark dataframe but i still havent found a solution. I want to subtract the values from consecutive columns in a dataframe. The operation I am describing can be seen in the image below. Bear in mind that the output dataframe wont have any values on first column as the first column in the input table cannot be subtracted by its previous one as it doesn't exist. 回答1: diff has an axis param so you can just do this in one step: In

问题 I want to calculate the mean of all the values in selected columns in a dataframe. For example, I have a dataframe with columns A, B, C, D and E and I want the mean of all the values in columns A, C and E. import pandas as pd df1 = pd.DataFrame( ( {'A': [1,2,3,4,5], 'B': [10,20,30,40,50], 'C': [11,21,31,41,51], 'D': [12,22,32,42,52], 'E': [13,23,33,43,53]} ) ) print( df1 ) print( "Mean of df1:", df1.mean() ) df2 = pd.concat( [df1['A'], df1['C'], df1['E'] ], ignore_index=True ) print( df2 )