How to change Datetime formate without converting to string

Question

I have a data frame that I'm trying to create a tsplot using seaborn, the first issue I'm having after converting my DateTime from string to a DateTime object is that the day had been automatically added.

The original data frame looks like this:

zillowvisualtop5.head()
Out[161]: 
        City_State     Year     Price
0     New York, NY  1996-04  169300.0
1  Los Angeles, CA  1996-04  157700.0
2      Houston, TX  1996-04   86500.0
3      Chicago, IL  1996-04  114000.0
6      Phoenix, AZ  1996-04   88100.0

(Note that the date is in year-month format) After I covert it into DateTime object so that I could plot it using seaborn, I get the issue of having a date added after the month.

zillowvisualtop5['Year'] = pd.to_datetime(zillowvisualtop5['Year'], format= '%Y-%m')
zillowvisualtop5.head()
Out[165]: 
        City_State       Year     Price
0     New York, NY 1996-04-01  169300.0
1  Los Angeles, CA 1996-04-01  157700.0
2      Houston, TX 1996-04-01   86500.0
3      Chicago, IL 1996-04-01  114000.0
6      Phoenix, AZ 1996-04-01   88100.0

The solution that I've found seems to suggest converting to strftime but I need my time to be in DateTime format so I can plot it using seaborn.

I also tried converting it to period which looked like it solved the problem, however then I am unable to plot it. — Lee
– Lee, Commented Dec 20, 2019 at 4:40

Roberto Moctezuma · Accepted Answer · 2019-12-20 06:04:50Z

1

The problem that you are having is that a DateTime object will always include all the components of a date object and a time object. There is no way to have a DateTime object that only has year and month info (source: here).

However, you can use the matplotlib converters like this:

import pandas as pd
from pandas.plotting import register_matplotlib_converters
import seaborn as sns

cols = ['City', 'Price', 'Month']
data = [['New York', 125, '1996-04'],
        ['New York', 79, '1996-05'],
        ['New York', 85, '1996-06'],
        ['Houston', 90, '1996-04'],
        ['Houston', 95, '1996-05'],
        ['Houston',127, '1996-06']]

df = pd.DataFrame(data, columns = cols)
print (df)

chart = sns.lineplot(x='Month', y='Price', hue='City', data=df)

Does that get the results you were looking for?

edited Dec 20, 2019 at 6:04

answered Dec 20, 2019 at 4:45

Roberto Moctezuma

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4 Comments

Lee Over a year ago

Sure, I'm trying to make a time series plot with time on the x-axis and price on the y-axis. There should be one line for each of the cities. I have done this already when my dataframe only has year. But when it's in the year-month format, I get this error while plotting: ``` ValueError: could not convert string to float: '1996-04' ```

Roberto Moctezuma Over a year ago

@Lee Thanks for clarifying, I hope the answer above works for you?

Lee Over a year ago

@ Roberto Moctezuma Thank you very much for your help! I guess I was approaching the problem wrong. I am using tsplot by the way. I was able to get a plot in the beginning without removing the automatically added day and the plot looked really smooth, the only problem was that my x-axis label was wrong. But now that I've removed the day using the method you've described, the graph looks very steplike which is weird and the label is off.

Lee Over a year ago

Thank you very much! Your last edit works! I switched over to using lineplot instead of tsplot.

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