Ggplot visualization improve-CodePudding

I have a data frame from a Bici service, it looks like this, where Origen_Id is the station's number, and Num_Viaje_Ori is the total number of trips that start in that station.

Origen_Id	Num_F	Num_M	Num_Viaje_Ori	Destino_Id	Num_F_d	Num_M_d	Num_Viaje_Des
11	1616	3973	5589	11	139	5 3855	5250
34	962	3232	4194	34	1340	4236	5576
35	1321	3993	5314	35	1418	4239	5657
50	1797	4293	6090	50	1785	4314	6099
51	1891	5186	7077	51	3084	7771	10855
52	1379	4320	5699	52	1299	3913	5212
54	1275	3950	5225	54	1373	4046	5419
75	1332	2939	4271	75	1202	2763	3965
194	1346	3792	5138	194	632	1845	2477
271	1511	3640	5151	271	1483	3750	5233

When I run

s<-ggplot(most, aes(x=Origen_Id, y=Num_Viaje_Ori)) geom_bar(stat="identity")

I got

How can I fix it?, I mean, how can I make the bars got closer?

CodePudding user response：

Implementing the commented suggestions, you should get:

library(tidyverse)
library(tibble)
library(ggthemes)

most <- 
  tibble::tribble(
  ~Origen_Id, ~Num_F, ~Num_M, ~Num_Viaje_Ori, ~Destino_Id, ~Num_F_d, ~Num_M_d, ~Num_Viaje_Des,
         11L,  1616L,  3973L,          5589L,         11L,     139L, "5 3855",          5250L,
         34L,   962L,  3232L,          4194L,         34L,    1340L,   "4236",          5576L,
         35L,  1321L,  3993L,          5314L,         35L,    1418L,   "4239",          5657L,
         50L,  1797L,  4293L,          6090L,         50L,    1785L,   "4314",          6099L,
         51L,  1891L,  5186L,          7077L,         51L,    3084L,   "7771",         10855L,
         52L,  1379L,  4320L,          5699L,         52L,    1299L,   "3913",          5212L,
         54L,  1275L,  3950L,          5225L,         54L,    1373L,   "4046",          5419L,
         75L,  1332L,  2939L,          4271L,         75L,    1202L,   "2763",          3965L,
        194L,  1346L,  3792L,          5138L,        194L,     632L,   "1845",          2477L,
        271L,  1511L,  3640L,          5151L,        271L,    1483L,   "3750",          5233L
  )

most %>% 
  mutate(Origen_Id = as.factor(Origen_Id)) %>% 
  ggplot(aes(x=Origen_Id, y=Num_Viaje_Ori))  
  geom_col(fill = "darkslateblue")   
  ggthemes::theme_economist_white()

^{Created on 2021-11-23 by the reprex package (v2.0.1)}