Matplotlib Default date format?

Question

I'm using Pandas to read a .csv file that a 'Timestamp' date column in the format:

31/12/2016 00:00

I use the following line to convert it to a datetime64 dtype:

time = pd.to_datetime(df['Timestamp'])

The column has an entry corresponding to every 15mins for almost a year, and I've run into a problem when I want to plot more than 1 months worth.

Pandas seems to change the format from ISO to US upon reading (so YYYY:MM:DD to YYYY:DD:MM), so my plots have 30 day gaps whenever the datetime represents a new day. A plot of the first 5 days looks like:

This is the raw data in the file either side of the jump:

01/01/2017 23:45
02/01/2017 00:00

If I print the values being plotted (after reading) around the 1st jump, I get:

2017-01-01 23:45:00
2017-02-01 00:00:00

So is there a way to get pandas to read the dates properly?

Thanks!

akuiper · Accepted Answer · 2017-09-03 18:50:56Z

1

You can specify a format parameter in pd.to_datetime to tell pandas how to parse the date exactly, which I suppose is what you need:

time = pd.to_datetime(df['Timestamp'], format='%d/%m/%Y %H:%M')

pd.to_datetime('02/01/2017 00:00')
#Timestamp('2017-02-01 00:00:00')

pd.to_datetime('02/01/2017 00:00', format='%d/%m/%Y %H:%M')
#Timestamp('2017-01-02 00:00:00')

answered Sep 3, 2017 at 18:50

akuiper

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