I'm trying to plot a pandas DataFrame with timestamps as index and int or float as columns:
| Time | Current_Gen1 | Current_Gen2 | Current_Gen3 | Current_100A_110V | Current_100A_220V | Current_shore_power | Gens_sum |
|---|---|---|---|---|---|---|---|
| 2022-04-01 19:00:00 | 44.011111 | 0.0 | 42.833333 | 2.000000 | 19.055556 | -0.066667 | 86.844444 |
| 2022-04-01 20:00:00 | 44.522222 | 0.0 | 43.616667 | 2.000000 | 17.861111 | -0.155556 | 88.138889 |
| 2022-04-01 21:00:00 | 45.155556 | 0.0 | 44.705556 | 2.005556 | 18.616667 | -0.161111 | 89.861111 |
| 2022-04-01 22:00:00 | 45.972222 | 0.0 | 45.372222 | 2.000000 | 19.133333 | -0.277778 | 91.344444 |
| 2022-04-01 23:00:00 | 45.677778 | 0.0 | 45.755556 | 2.000000 | 20.744444 | -0.377778 | 91.433333 |
I down sampled it to the hour to have fewer points to display
I want to display a major grid for the days and minor for the hours
If let the default settings, I get this graph :
import pandas as pd
import matplotlib.pyplot as plt
df = pd.read_csv(r"data.csv", index_col=['Time'], parse_dates=['Time'])
df2 = df.resample('H').mean()
fig_gen_sum, axe = plt.subplots()
df2.plot(ax=axe, y='Gens_sum', grid=True)
First issue: I don't understand why there is one date with the full description
And when I'm using formatter to get the days :
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.dates as dates
df = pd.read_csv(r"data.csv", index_col=['Time'], parse_dates=['Time'])
df2 = df.resample('H').mean()
fig_gen_sum, axe = plt.subplots()
df2.plot(ax=axe, y='Gens_sum', grid=True)
xax = axe.get_xaxis()
xax.set_major_formatter(dates.DateFormatter('%d-%m'))
xax.set_major_locator(dates.DayLocator())
Second issue: I'm getting a graph with days counted as hours if read it right
I've tried different configurations, but it always gives me weird result
I'm guessing the issue is with the formatting of my timestamps, but I can't find what
CodePudding user response：
@tdy gave the response in the comment of the post
The solution is to set the option x_compat=True like:
df2.plot(ax=axe,x='time', y='Gens_sum', grid=True, x_compat=True)
As specified in pandas documentation
Pandas includes automatic tick resolution adjustment for regular frequency time-series data. For limited cases where pandas cannot infer the frequency information (e.g., in an externally created twinx), you can choose to suppress this behavior for alignment purposes.
I can then get this result:
Everything else, including major and minor ticks works as well from there :
fig_gen_sum, axe = plt.subplots()
df2.plot(ax=axe,x='time', y='Gens_sum', grid=True, x_compat=True)
xax = axe.get_xaxis()
xax.set_major_locator(dates.DayLocator())
xax.set_major_formatter(dates.DateFormatter('%y/%m/%d'))
xax.set_minor_locator(dates.HourLocator(interval=5))
xax.set_minor_formatter(dates.DateFormatter('%H h'))
Gives:
