CODEWITHSUNDEEP
pythonpandasmatplotlib
Deeone
Deeone

Reputation: 163

Ticks which exceeds Locator.MAXTICKS

I am trying to plot a time-series data by HOUR as shown in the image, but I keep getting this error - Locator attempting to generate 91897 ticks ([15191.0, ..., 19020.0]), which exceeds Locator.MAXTICKS (1000). I have tried all available solutions on StackOverflow for similar problems but still could not get around it, Please help.

Link to image: https://drive.google.com/file/d/1b1PNCqVp7W65ciVPEWELiV2cTiXgBu2V/view?usp=sharing

Link to CSV: https://drive.google.com/file/d/113kYjsqbyL5wx1j204yK6Wmop4wLsqMQ/view?usp=sharing

Attempted codes:

%matplotlib inline
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.dates as md

df = pd.read_csv('price.csv', delimiter=',')

plt.rcParams['font.size'] = 18

fig, (ax) = plt.subplots(ncols=1, nrows=1, figsize=(20,15))

# Plot the data
ax.plot(df.VOLUME, label = 'volume')

# Set the title
ax.set_title("AUDUSD Hourly Variation\n",  fontsize=23)

# Set the Y-Axis label 
ax.set_ylabel("\nVolume")

# Set the X-Axis label
ax.set_xlabel('\nHour') 

ax.legend()                               # Plot the legend for axes


# apply locator and formatter to the ticks on the X axis
ax.xaxis.set_major_locator(md.HourLocator(interval = 1))    # X axis will be formatted in Hour
ax.xaxis.set_major_formatter(md.DateFormatter('%H'))      # set the date format to the hour shortname

# Set the limits (range) of the X-Axis
ax.set_xlim([pd.to_datetime('2011.08.05', format = '%Y.%m.%d'),
             pd.to_datetime('2022.01.28', format = '%Y.%m.%d')])


plt.tight_layout()

plt.show()

Thanks for your assistance.

Upvotes: 2

Views: 5506

Answers (1)

ToolmakerSteve
ToolmakerSteve

Reputation: 21357

According to the error message, you are attempting to plot a time range that covers ~4000 hours (19000 - 15000 = 4000), but are only allowed to have max 1000 ticks. Increase the interval to 4 or 5.

ax.xaxis.set_major_locator(md.HourLocator(interval = 5))

Perhaps . doesn't work well as a separator in dates (because it is also used as a decimal separator in numbers). Try:

ax.set_xlim([pd.to_datetime('2011-08-05', format = '%Y-%m-%d'),
             pd.to_datetime('2022-01-28', format = '%Y-%m-%d')])

If that doesn't cause the error, then change your input data correspondingly.

Upvotes: 2

Related Questions