plotting three variables using ggplot
i'm trying to make a bar chart to show the average speed of shipping per category per year. my data set is like the following

category | order.date | speed

stationary | 2010-5-6 | 3

supplies | 2011-5-6 | 5

technology | 2014-5-6 | 3

…
is this the sort of output you want?

library(tidyverse)

library(lubridate)

westdata <- tibble::tribble(

~category, ~order.date, ~speed,

"stationary", "2010-05-06", 3,

"supplies", "2011-05-06", 5,

"technology", "2014-05-06", 3,

"supplies", "2013-05-06", 2,

…
aggregate supply indicates the total amount of goods and services produced within an economy at a given the general (or overall) price level during an accounting period. `as = f(barn,barl,bark,bart)` where,as = aggregate supplyn = natural resourcesl = labourk = stock of capitalt = state of technologynatural resources: natural resources include the gifts of nature such as fertile land, weather conditions, adequate rainfall, flora and fauna, perennial rivers etc. the abundant availability of all these factors act in favour of production. the aggregate supply of a country bestowed with these natural resources will be higher and vice-versa.labour: availability of skilled and motivated labour is another determinant of supply. the supply in an economy with abundance of skilled labour will be high and vice-versa.capital: capital is essential in the production process. capital helps in acquiring raw materials, equipments, plant and machinery, buildings etc. which are essential for increasing the production. greater the stock of capital, greater would be the level of output and production. state of technology: the state of technology in an economy decides the level of supply. advanced technology helps in improving the production efficiency in a a country. with better and advanced technology production can be increased while reducing the cost of production. this in turn positively affects the supply. thus, the availability of modern and advanced technology helps in increasing the supply. hii..

according to me,the cut off will be around 90-95 marks for general category,50-55 marks for obc category,35-40 marks for sc category and 25-30 marks for st category.so it is difficult to be predict now.

please see the table below for previous years trends:-

 

jee main cut off trends (2013-2017)

| s.no. | category | 2017 | 2016 | 2015 | 2014 | 2013 |
| 1 | general | 81 | 100 | 105 | 115 | 113 |
| 2 | obc-ncl | 49 | 70 | 70 | 74 | 70 |
| 3 | sc | 32 | 52 | 50 | 53 | 50 |
| 4 | st | 27 | 48 | 44 | 47 | 45 | histogram  divide data o equal width o no overlapping  bar chart o skew­ pulls direction of mean o symmetric numeric summary center, spread, and location  greek letters for population  roman letters for statistics 1. mean  µ= population mean  x bar= sanple mean o ∑ xi  all over n= sample mean  k=0 2. mean vs. median a. mean used the most b. n is small when outliers occur c. use median, mean is too affected spread 1. range (max­min) a. sensitive to outliers 2. iqr a. not sensitive to outliers variability­ xi­x bar ?answer :
step 1 of 1 :


in a pareto chart, the bars are always arranged in descending order according to frequencies.
the pareto chart helps us understand data by drawing attention to the more important categories, which have the highest frequencies. there are websites that give you technical analysis indicators (including golden crosses and death crosses) such as

https://www.stockmonitor.com/stock-screener/death-cross-50ma-cross-down-200ma/

or you can simply graph the moving averages yourself.

i am not a big fan of technical analysis indicators so i have never used them. ok so, you're simply making a wrong aggregation in your y-axis. what you want to do is make 3 aggregations of type sum, each one for a specific category (men-women-children), like the following:

[[image]](https://aws1.discourse-cdn.com/elastic/original/3x/4/4/441907755076ca3a9417b959036a79f906d45448.png "image")

though, if you want to make something more professional and good-looking, since you're interes… hi paul,

i believe the financial reporting covers in quite a lot of detail exactly what you are looking for.

from what i can tell you aren’t using templates in your tables…

[[image]](https://forum.enterprisedna.co/uploads/db7134/original/2x/5/559a333f85c159c8d9bec9235ca5c45997d08858.png "image")

if you want to get a certain order and custom table then you really need to use the template approach covered in t… here is an example notebook

<https://gist.github.com/volkerh/465925d24accc940f7a0a0b1f5f40f7a#file-map_array_example-ipynb>

map\_array\_example.ipynb

{

"cells": [

{

"cell\_type": "code",

"execution\_count": 1,

"id": "satellite-momentum",

"metadata": {},

"outputs": [],

"source… hi @sam\_cat - there was another topic on this query. i can't find it, so i've tweaked yours to make it more searchable moving forwards. 

this is to do with the direct debit figure. we look at your prices for the two year plan, and the annual consumption of the property, getting an annual spend and a monthly cost (if you divide that figure by 12). the tariff that you're on now just displays your current direct debit, which will of course take into account your current credit balance. 

tim sylvia frank chlh 274 homework problems chapter 3 1. a. crude death rate: total populace death in a specific span-time at the mean year. b. age-specific rate: total incidence occurred in a specific-age group of the populace in a specific span time. c. cause-specific rate: total death of a populace from a specific-cause in a specific span-time at the mean year. d. proportional mortality ratio: total death within a populace due to a specific-cause divided by the total death in the populace e. maternal mortality rate: incidence of death because of birth of a child or due to pregnancy associated complications. f. infant mortality rate: rate of event of newborn death over a year by birth of newborn over a same interval. g. neonatal mortality