Closed as not planned
Description
Bug summary
After applying a
df1.resample('10S').asfreq()
transformation to a timeseries pandas dataframe I get an OverflowError error when trying to format the X-axis.
Before the transformation the ploting works.
Code for reproduction
# %%
from io import StringIO
import matplotlib.dates as mdates
import matplotlib.pyplot as plt
import pandas as pd
import matplotlib
print (matplotlib.__version__)
import platform
print (platform.python_version())
# %%
df1 = pd.read_csv(StringIO(
'ts,DE0008469008,MBI000000006\r\n2023-03-31 12:12:09,15576.57,15579.0\r\n2023-03-31 12:12:10,15576.66,\r\n2023-03-31 12:12:13,,15580.9\r\n2023-03-31 12:12:15,15576.74,15581.9\r\n2023-03-31 12:12:16,15577.0,15581.8\r\n2023-03-31 12:12:17,15577.3,15581.7\r\n2023-03-31 12:12:19,,15580.8\r\n2023-03-31 12:12:20,,15582.0\r\n2023-03-31 12:12:21,15577.68,15581.8\r\n2023-03-31 12:12:22,,15581.3\r\n2023-03-31 12:12:23,15577.64,\r\n2023-03-31 12:12:24,15577.82,\r\n2023-03-31 12:12:25,15577.92,15582.4\r\n2023-03-31 12:12:26,15578.19,\r\n2023-03-31 12:12:28,15578.69,15581.7\r\n2023-03-31 12:12:29,,15582.0\r\n2023-03-31 12:12:30,15578.85,\r\n2023-03-31 12:12:31,15578.76,\r\n2023-03-31 12:12:33,15578.57,\r\n2023-03-31 12:12:34,15578.65,\r\n2023-03-31 12:12:35,,15584.0\r\n2023-03-31 12:12:37,,15584.2\r\n2023-03-31 12:12:38,,15583.4\r\n2023-03-31 12:12:40,15578.57,\r\n2023-03-31 12:12:41,15578.49,15581.8\r\n2023-03-31 12:12:42,,15582.3\r\n2023-03-31 12:12:44,,15581.5\r\n2023-03-31 12:12:45,15578.54,15580.3\r\n2023-03-31 12:12:46,,15580.6\r\n2023-03-31 12:12:47,,15580.3\r\n'),
index_col='ts', parse_dates=['ts'])
# %%
df2 = df1.resample('10S').asfreq().ffill().dropna(axis=0, how='all')
# %%
def plotme(df):
fig, ax = plt.subplots()
df.plot(ax=ax, linewidth=0.5)
hours = mdates.HourLocator(interval=1)
h_fmt = mdates.DateFormatter('%H')
ax.xaxis.set_major_locator(hours)
ax.xaxis.set_major_formatter(h_fmt)
# %%
plotme(df1)
# %%
plotme(df2)Actual outcome
358 dt = (np.datetime64(get_epoch()) +
--> 359 np.timedelta64(int(np.round(x * MUSECONDS_PER_DAY)), 'us'))
360 if dt < np.datetime64('0001-01-01') or dt >= np.datetime64('10000-01-01'):
361 raise ValueError(f'Date ordinal {x} converts to {dt} (using '
362 f'epoch {get_epoch()}), but Matplotlib dates must be '
363 'between year 0001 and 9999.')
OverflowError: int too big to convert
Expected outcome
The transformed dataframe can be plotted
Additional information
No response
Operating system
Windows 11
Matplotlib Version
3.7.1
Matplotlib Backend
module://matplotlib_inline.backend_inline
Python version
3.9
Jupyter version
jupyterlab 3.6.3
Installation
conda