Displaying 4 results from an estimated 4 matches for "df_sort".
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do_sort
2012 Jul 18
2
How to have original (name) order after melt and cast command
...6320
23 2012-03-26 lmn 10.203993350
24 2012-03-23 lmn 10.229667040
25 2012-03-22 lmn 10.209677420
26 2012-03-21 lmn 10.229277930
27 2012-03-20 lmn 10.024391920
attach(dat1)
library(plyr)
library(reshape)
in.melt <- melt(dat1, measure = 'rate')
(df = cast(in.melt, date ~ name))
df_sorted = df[order(as.Date(df$date, "%m/%d/%Y"), decreasing = TRUE),]
> df_sorted
date abc lmn xyz
9 2012-03-30 5.550737 10.11885 0.065550707
8 2012-03-29 4.877621 10.18570 0.001825007
7 2012-03-28 5.462477 10.04977 0.054441969
6 2012-03-27 4.972...
2010 Aug 27
1
Band-wise Sum
...430325.24, 1180946.57, 150000, 167490, 81255.16, 54812.5, 3000, 1275702.94, 9100, 1763142.3, 3283048.61, 1200000, 11800, 3000, 96894.02, 453671.72, 7590, 106065.24, 940711.67, 2443000, 9500000, 39000, 1501939.67)
## First I have sorted the data rating-wise as
df <- data.frame(rating, ead)
df_sorted <-
df[order(df$rating),]
df_sorted_AAA <- subset(df_sorted, rating=="AAA")
df_sorted_AA <- subset(df_sorted, rating=="AA")
df_sorted_A <- subset(df_sorted, rating=="A")
df_sorted_BBB <- subset(df_sorted, rating=="BBB")
df_sorted_BB &l...
2010 Aug 30
2
Band-wise Conditional Sum - Actual problem
...255.16, 54812.5, 3000, 1275702.94, 9100, 1763142.3, 3283048.61, 1200000, 11800, 3000, 96894.02, 453671.72, 7590, 106065.24, 940711.67, 2443000, 9500000, 39000, 1501939.67)
df$ead.cat <- cut(df$ead, breaks=c(0, 100000, 500000, 1000000, 2000000, 5000000 , 10000000, 100000000) )
df
df_sorted <- df[order(df$rating),] # the output is as given below.
> df_sorted
rating ead ead.cat
1
A 169229.93 (1e+05,5e+05]
3 A 5877794.25 (5e+06,1e+07]
6 A 21000.00 (0,1e+05]
12 A ...
2013 Apr 15
6
Sorting data.frame and again sorting within data.frame
... values
A 4/15/2013 31
A 4/14/2013 102
A 4/13/2013 31
B 4/15/2013
34
B 4/14/2013 47
B 4/13/2013 17
C 4/15/2013 10
C 4/14/2013 29
C 4/13/2013 11
I tried
df_sorted = df[order(df$names, (as.Date(df$dates, "%m/%d/%Y")), decreasing = TRUE),]
> df_sorted
names dates values
1 C 4/15/2013 10
9 C 4/14/2013 29
5 C 4/13/2013
11
6 B 4/15/2013 34
8 B 4/14/2013 47
4 B 4/13/2013 17
3 A 4/15/2013 ...