我有以下数据集:
https://app.box.com/s/au58xaw60r1hyeek5cua6q20byumgvmj
我想根据一天中的时间创建密度图。这是我到目前为止所做的:
library("ggplot2")
library("scales")
library("lubridate")
timestamp_df$timestamp_time <- format(ymd_hms(hn_tweets$timestamp), "%H:%M:%S")
ggplot(timestamp_df, aes(timestamp_time)) +
geom_density(aes(fill = ..count..)) +
scale_x_datetime(breaks = date_breaks("2 hours"),labels=date_format("%H:%M"))
它给出以下错误:
Error: Invalid input: time_trans works with objects of class POSIXct only
如果我将其转换为POSIXct
,则会为数据添加日期。
更新1
以下转换数据为'NA'
timestamp_df$timestamp_time <- as.POSIXct(timestamp_df$timestamp_time, format = "%H:%M%:%S", tz = "UTC"
更新2
答案 0 :(得分:0)
这是一种方法:
library(ggplot2)
library(lubridate)
library(scales)
df <- read.csv("data.csv") #given in OP
将字符转换为POSIXct
df$timestamp <- as.POSIXct(strptime(df$timestamp, "%m/%d/%Y %H:%M", tz = "UTC"))
library(hms)
提取小时和分钟:
df$time <- hms::hms(second(df$timestamp), minute(df$timestamp), hour(df$timestamp))
再次转换为POSIXct
,因为ggplot不适用于类hms
。
df$time <- as.POSIXct(df$time)
ggplot(df, aes(time)) +
geom_density(fill = "red", alpha = 0.5) + #also play with adjust such as adjust = 0.5
scale_x_datetime(breaks = date_breaks("2 hours"), labels=date_format("%H:%M"))
将其缩放为1:
ggplot(df) +
geom_density( aes(x = time, y = ..scaled..), fill = "red", alpha = 0.5) +
scale_x_datetime(breaks = date_breaks("2 hours"), labels=date_format("%H:%M"))
其中..scaled..
是创建绘图时stat_density
的计算变量。