I'd like to reproduce this image from this link. But I got this weird result.

This is fairly straightforward. I'd like to plot a time series from a dataframe. It's not a xts type of data. It's just a simple dataframe. Date is already recognized as date. Not sure, why ggplot is showing this erratic lines instead of geom\_line.

Can anyone let me know why? Thanks in advance!

[tutorial original source](http://rwanjohi.rbind.io/2018/04/05/time-series-forecasting-using-lstm-in-r/)

This is the desired output.
[![desired output](https://i.stack.imgur.com/k2QFg.png)](https://i.stack.imgur.com/k2QFg.png)

This is my output...
[![my output](https://i.stack.imgur.com/h7svd.png)](https://i.stack.imgur.com/h7svd.png)

My reproducible code:

```
library(ggplot2)

colnames(data)<-c("date","value")
data$date <- as.Date(data$date, "%m/%d/%Y")

ggplot(data, aes(x = date, y = value)) + geom_line()

```

data dput is here:

```
structure(list(date = structure(c(13514, 13545, 13573, 13604, 
13634, 13665, 13695, 13726, 13757, 13787, 13818, 13848, 13879, 
13910, 13939, 13970, 14000, 14031, 14061, 14092, 14123, 14153, 
14184, 14214, 14245, 14276, 14304, 14335, 14365, 14396, 14426, 
14457, 14488, 14518, 14549, 14579, 14610, 14641, 14669, 14700, 
14730, 14761, 14791, 14822, 14853, 14883, 14914, 14944, 14975, 
15006, 15034, 15065, 15095, 15126, 15156, 15187, 15218, 15248, 
15279, 15309, 15340, 15371, 15400, 15431, 15461, 15492, 15522, 
15553, 15584, 15614, 15645, 15675, 15706, 15737, 15765, 15796, 
15826, 15857, 15887, 15918, 15949, 15979, 16010, 16040, 16071, 
16102, 16130, 16161, 16191, 16222, 16252, 16283, 16314, 16344, 
16375, 16405, 16436, 16467, 16495, 16526, 16556, 16587, 16617, 
16648, 16679, 16709, 16740, 16770, 16801, 16832, 16861, 16892, 
16922, 16953, 16983, 17014, 17045, 17075, 17106, 17136, 17167, 
17198, 17226, 17257, 17287, 17318, 17348, 17379, 17410, 17440, 
17471, 17501, 17532, 17563, 17591, 13514, 13545, 13573, 13604, 
13634, 13665, 13695, 13726, 13757, 13787, 13818, 13848, 13879, 
13910, 13939, 13970, 14000, 14031, 14061, 14092, 14123, 14153, 
14184, 14214, 14245, 14276, 14304, 14335, 14365, 14396, 14426, 
14457, 14488, 14518, 14549, 14579, 14610, 14641, 14669, 14700, 
14730, 14761, 14791, 14822, 14853, 14883, 14914, 14944, 14975, 
15006, 15034, 15065, 15095, 15126, 15156, 15187, 15218, 15248, 
15279, 15309, 15340, 15371, 15400, 15431, 15461, 15492, 15522, 
15553, 15584, 15614, 15645, 15675, 15706, 15737, 15765, 15796, 
15826, 15857, 15887, 15918, 15949, 15979, 16010, 16040, 16071, 
16102, 16130, 16161, 16191, 16222, 16252, 16283, 16314, 16344, 
16375, 16405, 16436, 16467, 16495, 16526, 16556, 16587, 16617, 
16648, 16679, 16709, 16740, 16770, 16801, 16832, 16861, 16892, 
16922, 16953, 16983, 17014, 17045, 17075, 17106, 17136, 17167, 
17198, 17226, 17257, 17287, 17318, 17348, 17379, 17410, 17440, 
17471, 17501, 17532, 17563, 17591, 13514, 13545, 13573, 13604, 
13634, 13665, 13695, 13726, 13757, 13787, 13818, 13848, 13879, 
13910, 13939, 13970, 14000, 14031, 14061, 14092, 14123, 14153, 
14184, 14214, 14245, 14276, 14304, 14335, 14365, 14396, 14426, 
14457, 14488, 14518, 14549, 14579, 14610, 14641, 14669, 14700, 
14730, 14761, 14791, 14822, 14853, 14883, 14914, 14944, 14975, 
15006, 15034, 15065, 15095, 15126, 15156, 15187, 15218, 15248, 
15279, 15309, 15340, 15371, 15400, 15431, 15461, 15492, 15522, 
15553, 15584, 15614, 15645, 15675, 15706, 15737, 15765, 15796, 
15826, 15857, 15887, 15918, 15949, 15979, 16010, 16040, 16071, 
16102, 16130, 16161, 16191, 16222, 16252, 16283, 16314, 16344, 
16375, 16405, 16436, 16467, 16495, 16526, 16556, 16587, 16617, 
16648, 16679, 16709, 16740, 16770, 16801, 16832, 16861, 16892, 
16922, 16953, 16983, 17014, 17045, 17075, 17106, 17136, 17167, 
17198, 17226, 17257, 17287, 17318, 17348, 17379, 17410, 17440, 
17471, 17501, 17532, 17563, 17591), class = "Date"), value = c(4.76, 
4.72, 4.56, 4.69, 4.75, 5.1, 5, 4.67, 4.52, 4.53, 4.15, 4.1, 
3.74, 3.74, 3.51, 3.68, 3.88, 4.1, 4.01, 3.89, 3.69, 3.81, 3.53, 
2.42, 2.52, 2.87, 2.82, 2.93, 3.29, 3.72, 3.56, 3.59, 3.4, 3.39, 
3.4, 3.59, 3.73, 3.69, 3.73, 3.85, 3.42, 3.2, 3.01, 2.7, 2.65, 
2.54, 2.76, 3.29, 3.39, 3.58, 3.41, 3.46, 3.17, 3, 3, 2.3, 1.98, 
2.15, 2.01, 1.98, 1.97, 1.97, 2.17, 2.05, 1.8, 1.62, 1.53, 1.68, 
1.72, 1.75, 1.65, 1.72, 1.91, 1.98, 1.96, 1.76, 1.93, 2.3, 2.58, 
2.74, 2.81, 2.62, 2.72, 2.9, 2.86, 2.71, 2.72, 2.71, 2.56, 2.6, 
2.54, 2.42, 2.53, 2.3, 2.33, 2.21, 1.88, 1.98, 2.04, 1.94, 2.2, 
2.36, 2.32, 2.17, 2.17, 2.07, 2.26, 2.24, 2.09, 1.78, 1.89, 1.81, 
1.81, 1.64, 1.5, 1.56, 1.63, 1.76, 2.14, 2.49, 2.43, 2.42, 2.48, 
2.3, 2.3, 2.19, 2.32, 2.21, 2.2, 2.36, 2.35, 2.4, 2.58, 2.86, 
2.84, 5.32, 5.31, 5.3, 5.31, 5.31, 5.33, 5.32, 5.49, 5.46, 5.08, 
4.97, 5.02, 3.84, 3.06, 2.79, 2.85, 2.66, 2.76, 2.79, 2.79, 3.59, 
4.32, 2.36, 1.77, 1.02, 1.16, 1.07, 0.89, 0.57, 0.39, 0.35, 0.3, 
0.25, 0.24, 0.21, 0.22, 0.2, 0.19, 0.23, 0.3, 0.45, 0.52, 0.41, 
0.32, 0.28, 0.27, 0.27, 0.3, 0.29, 0.28, 0.28, 0.23, 0.21, 0.22, 
0.24, 0.29, 0.33, 0.37, 0.41, 0.49, 0.4, 0.3, 0.29, 0.29, 0.29, 
0.32, 0.3, 0.26, 0.24, 0.23, 0.23, 0.24, 0.23, 0.22, 0.21, 0.2, 
0.2, 0.19, 0.14, 0.12, 0.11, 0.12, 0.12, 0.14, 0.12, 0.13, 0.12, 
0.12, 0.11, 0.11, 0.13, 0.13, 0.12, 0.12, 0.13, 0.15, 0.16, 0.15, 
0.14, 0.13, 0.15, 0.18, 0.19, 0.26, 0.27, 0.25, 0.3, 0.54, 0.57, 
0.54, 0.55, 0.55, 0.57, 0.55, 0.62, 0.73, 0.75, 0.72, 0.71, 0.87, 
0.9, 0.87, 0.98, 1.03, 1.05, 1.16, 1.22, 1.25, 1.25, 1.26, 1.32, 
1.54, 1.63, 1.78, 2.08, 5.25, 5.26, 5.26, 5.25, 5.25, 5.25, 5.26, 
5.02, 4.94, 4.76, 4.49, 4.24, 3.94, 2.98, 2.61, 2.28, 1.98, 2, 
2.01, 2, 1.81, 0.97, 0.39, 0.16, 0.15, 0.22, 0.18, 0.15, 0.18, 
0.21, 0.16, 0.16, 0.15, 0.12, 0.12, 0.12, 0.11, 0.13, 0.16, 0.2, 
0.2, 0.18, 0.18, 0.19, 0.19, 0.19, 0.19, 0.18, 0.17, 0.16, 0.14, 
0.1, 0.09, 0.09, 0.07, 0.1, 0.08, 0.07, 0.08, 0.07, 0.08, 0.1, 
0.13, 0.14, 0.16, 0.16, 0.16, 0.13, 0.14, 0.16, 0.16, 0.16, 0.14, 
0.15, 0.14, 0.15, 0.11, 0.09, 0.09, 0.08, 0.08, 0.09, 0.08, 0.09, 
0.07, 0.07, 0.08, 0.09, 0.09, 0.1, 0.09, 0.09, 0.09, 0.09, 0.09, 
0.12, 0.11, 0.11, 0.11, 0.12, 0.12, 0.13, 0.13, 0.14, 0.14, 0.12, 
0.12, 0.24, 0.34, 0.38, 0.36, 0.37, 0.37, 0.38, 0.39, 0.4, 0.4, 
0.4, 0.41, 0.54, 0.65, 0.66, 0.79, 0.9, 0.91, 1.04, 1.15, 1.16, 
1.15, 1.15, 1.16, 1.3, 1.41, 1.42, 1.51)), row.names = c(NA, 
-405L), class = "data.frame")

```