Plotting pd.Series object does not show year correctly
I am graphing the results of the measurements of a humidity sensor over time.
I'm using Python 3.7.1 and Pandas 0.24.2.

I have a list called dateTimeList with date and time strings:

```
dateTimeList = ['15.3.2019 11:44:27', '15.3.2019 12:44:33', '15.3.2019 13:44:39']
```

I wrote this code where `index` is a DatetimeIndex object and `humList` is a list of floats.

```python
	index = pd.to_datetime(dateTimeList, format='%d.%m.%Y %H:%M:%S')
	ts = pd.Series(humList, index)

	plt.figure(figsize=(12.80, 7.20))
	ts.plot(title='Gráfico de Humedad en el Tiempo', style='g', marker='o')
	
	plt.xlabel('Tiempo [días]')
	plt.ylabel('Humedad [V]')
	plt.grid()
	plt.savefig('Hum_General'+'.png', bbox_inches='tight')
	plt.show()
```

And I have this two results, one with data from February[1] and the other one with data from March[2].

The problem is that in March instead of leaving the year 2019, sequences of 00 12 00 12 appear on the x axis. I think it is important to note that this only happens on the data of March, since February is ok, and the data of both months have the same structure. Day and Month are shown correctly on both plots.

  [1]: https://www.dropbox.com/s/ckv6zeqb0psh6ih/Hum_General_Febrero.png?dl=0
  [2]: https://www.dropbox.com/s/nzvbwnuf5fkuim1/Hum_General_Marzo.png?dl=0

I also tried with:

```
index = [ pd.to_datetime(date, format='%d.%m.%Y %H:%M:%S') for date in dateTimeList]
```

Now `index` is a list of Timestamps objects. Same Results.

Full Code, Data and Outputs:
[CodeandData.zip](https://github.com/pandas-dev/pandas/files/2997619/CodeandData.zip)


