search for: df_select

...lt;- read.csv("test2.csv",header =TRUE) df_bs_id3 <- read.csv("test3.csv",header =TRUE) How could I would implement a code loop that , for instance, would select two coluns of interest in a fashion of the code below ? # selecting only 2 columns of interest for (1, 1:3) { df_selected [i] <- df_bs_id[i] [ , c("column1", "column2")] } Tks MMS [[alternative HTML version deleted]]

...alid_time <- as.POSIXct(df$valid_time, origin = "1970-01-01") # Extract year, month, day, and hour from valid_time df$Year <- year(df$valid_time) df$Month <- month(df$valid_time) df$Day <- day(df$valid_time) df$Hour <- hour(df$valid_time) # Select only the desired columns df_selected <- df %>% select(Year, Month, Day, Hour, tcc, t2m, RH) # Save the updated DataFrame to an Excel file write.xlsx(df_selected, excel_file_path, row.names = FALSE) -- Best Regards Javad Bayat M.Sc. Environment Engineering Alternative Mail: bayat194 at yahoo.com [[alternative HTML ver...

...rigin = "1970-01-01") > > # Extract year, month, day, and hour from valid_time > df$Year <- year(df$valid_time) > df$Month <- month(df$valid_time) > df$Day <- day(df$valid_time) > df$Hour <- hour(df$valid_time) > > # Select only the desired columns > df_selected <- df %>% select(Year, Month, Day, Hour, tcc, t2m, RH) > > # Save the updated DataFrame to an Excel file > write.xlsx(df_selected, excel_file_path, row.names = FALSE) > > > > > > > -- > Best Regards > Javad Bayat > M.Sc. Environment Engineering > Al...

...; > # Extract year, month, day, and hour from valid_time > > df$Year <- year(df$valid_time) > > df$Month <- month(df$valid_time) > > df$Day <- day(df$valid_time) > > df$Hour <- hour(df$valid_time) > > > > # Select only the desired columns > > df_selected <- df %>% select(Year, Month, Day, Hour, tcc, t2m, RH) > > > > # Save the updated DataFrame to an Excel file > > write.xlsx(df_selected, excel_file_path, row.names = FALSE) > > > > > > > > > > > > > > -- > > Best Regards >...

...month, day, and hour from valid_time >>> df$Year <- year(df$valid_time) >>> df$Month <- month(df$valid_time) >>> df$Day <- day(df$valid_time) >>> df$Hour <- hour(df$valid_time) >>> >>> # Select only the desired columns >>> df_selected <- df %>% select(Year, Month, Day, Hour, tcc, t2m, RH) >>> >>> # Save the updated DataFrame to an Excel file >>> write.xlsx(df_selected, excel_file_path, row.names = FALSE) >>> >>> >>> >>> >>> >>> >&g...

...ime > >>> df$Year <- year(df$valid_time) > >>> df$Month <- month(df$valid_time) > >>> df$Day <- day(df$valid_time) > >>> df$Hour <- hour(df$valid_time) > >>> > >>> # Select only the desired columns > >>> df_selected <- df %>% select(Year, Month, Day, Hour, tcc, t2m, RH) > >>> > >>> # Save the updated DataFrame to an Excel file > >>> write.xlsx(df_selected, excel_file_path, row.names = FALSE) > >>> > >>> > >>> > >>> >...

...Year <- year(df$valid_time) >> >>> df$Month <- month(df$valid_time) >> >>> df$Day <- day(df$valid_time) >> >>> df$Hour <- hour(df$valid_time) >> >>> >> >>> # Select only the desired columns >> >>> df_selected <- df %>% select(Year, Month, Day, Hour, tcc, t2m, RH) >> >>> >> >>> # Save the updated DataFrame to an Excel file >> >>> write.xlsx(df_selected, excel_file_path, row.names = FALSE) >> >>> >> >>> >> >>...

...$Year <- year(df$valid_time) >> >>> df$Month <- month(df$valid_time) >> >>> df$Day <- day(df$valid_time) >> >>> df$Hour <- hour(df$valid_time) >> >>> >> >>> # Select only the desired columns >> >>> df_selected <- df %>% select(Year, Month, Day, Hour, tcc, t2m, RH) >> >>> >> >>> # Save the updated DataFrame to an Excel file >> >>> write.xlsx(df_selected, excel_file_path, row.names = FALSE) >> >>> >> >>> >> >>&gt...

...) > >> >>> df$Month <- month(df$valid_time) > >> >>> df$Day <- day(df$valid_time) > >> >>> df$Hour <- hour(df$valid_time) > >> >>> > >> >>> # Select only the desired columns > >> >>> df_selected <- df %>% select(Year, Month, Day, Hour, tcc, t2m, RH) > >> >>> > >> >>> # Save the updated DataFrame to an Excel file > >> >>> write.xlsx(df_selected, excel_file_path, row.names = FALSE) > >> >>> > >> >>...