Setting minute minor ticks for 1-second sampled data raises: OverflowError: int too big to convert

Consider this dataframe with a sample interval of 1 second that spans about 30 minutes:

import matplotlib.pyplot as plt
from matplotlib.dates import MinuteLocator
import pandas as pd

ndex = pd.date_range('2021-08-01 07:07:07', '2021-08-01 07:41:12', freq='1S', name='Time') 
df = pd.DataFrame(data=np.random.randint(1, 100, len(ndex)), index=ndex, columns=['A'])

And now we plot it:

fig, ax = plt.subplots()
df.plot(color='red', marker='x', lw=0, ms=0.2, ax=ax)

Which creates a plot without any complaints:

Now I'd like to have minor ticks at every minute.

I've tried this:

ax.xaxis.set_minor_locator(MinuteLocator())

But that fails with OverflowError: int too big to convert

CodePudding user response：

• 

  pandas.DataFrame.plot.scatter

  • Also pandas.DataFrame.plot with kind='scatter'
    • ax = df.reset_index().plot(kind='scatter', x='Time', y='A', color='red', marker='x', figsize=(25, 6), rot=90)

  # reset the index so Time will be a column to assign to x
  ax = df.reset_index().plot.scatter(x='Time', y='A', color='red', marker='x', figsize=(25, 6), rot=90)
  ax.xaxis.set_major_locator(mdates.MinuteLocator())
  

  

  ---

  • Note the difference in the xticks produced by the two methods

  pandas.DataFrame.plot xticks

  ax = df.plot(color='red', marker='x', lw=0, ms=0.2, figsize=(25, 6))
  
  ticks = ax.get_xticks()
  print(ticks)
  [out]:
  array([1627801627, 1627803672], dtype=int64)
  

  matplotlib.pyplot.scatter xticks

  fig, ax = plt.subplots(figsize=(25, 6))
  ax.scatter(x=df.index, y=df.A, color='red', marker='x')
  
  ticks2 = ax.get_xticks()
  print(ticks2)
  
  [out]:
  array([18840.29861111, 18840.30208333, 18840.30555556, 18840.30902778,
         18840.3125    , 18840.31597222, 18840.31944444])