matplotlib is not automatically reading dataframe as date

Question

Since pandas last update, the x axis is not reading the index as a date. Any clues on what changed? As an example, the following code (Source) creates a random df. The matplotlib part is exactly what I'm have been doing with my real dataset (dates in my data where made using time.strftime("%Y-%m-%d")):

import pandas as pd
import numpy as np
from datetime import datetime, timedelta
date_today = datetime.now()
days = pd.date_range(date_today, date_today + timedelta(7), freq='D')
np.random.seed(seed=1111)
data = np.random.randint(1, high=100, size=len(days))
df = pd.DataFrame({'test': days, 'col2': data})
df = df.set_index('test')
# creates graph:
import matplotlib.pyplot as plt
fig = plt.plot(df.index, df["col2"])
fig = plt.xticks(rotation=30), plt.legend(loc='best'), plt.xlabel("Weeks")
fig = plt.style.use(['bmh', 'seaborn-paper'])
fig = plt.title("Index", fontsize=14, fontweight='bold')
plt.show()

The resulting graph has the x axis in number format. Before updating, my graphs automatically had dates in the index (because the index is in date format).

When I run your code, I am gettting x-axis in the format of dates, YYYY-MM-DD. You my try resetting rcdefaults(). import matplotlib as mpl mpl.rcdefaults(). — Scott Boston
– Scott Boston, Commented Dec 27, 2017 at 23:13

Jody Klymak · Accepted Answer · 2018-01-03 21:57:55Z

1

Pandas used to import the units handlers for datetime64, but as of 0.21 stopped (though it may be back for 0.22). The way to get the old behaviour without explicit conversion is

from pandas.tseries import converter as pdtc
pdtc.register()

answered Jan 3, 2018 at 21:57

Jody Klymak

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Comments

Mike Müller · Accepted Answer · 2017-12-27 23:30:51Z

1

Solution 1

Use pandas .plot on the dataframe:

import pandas as pd
import numpy as np
from datetime import datetime, timedelta
date_today = datetime.now()
days = pd.date_range(date_today, date_today + timedelta(7), freq='D')
np.random.seed(seed=1111)
data = np.random.randint(1, high=100, size=len(days))
df = pd.DataFrame({'test': days, 'col2': data})
df = df.set_index('test')
# creates graph:
import matplotlib.pyplot as plt
sub = df.plot()
fig = plt.xticks(rotation=30), plt.legend(loc='best'), plt.xlabel("Weeks")
fig = plt.style.use(['bmh', 'seaborn-paper'])
fig = plt.title("Index", fontsize=14, fontweight='bold')

Solution 2

Convert them Python datetime objects:

fig = plt.plot(df.index.to_pydatetime(), df["col2"])

Result of both approaches

edited Dec 27, 2017 at 23:30

answered Dec 27, 2017 at 23:23

Mike Müller

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1 Comment

egodial Over a year ago

Both are elegant solutions! and worked. I'll stick with #2 because it does not add further lines to my code. Thank you! Edit: Thanks for the edits.

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