TypeError: float() argument must be a string or a number, not 'datetime.time' in relation with a scatter plot

Question

i have created the following DataFrame: date_merge as an example, because i actually want to display the temperature values throughout the day.

df_time = filtered_df_date["longtime"].dt.time
df_date = filtered_df_date["longtime"].dt.date

filtered_df_date:

index	longtime
52754	2020-01-01 00:00:00
52755	2020-01-01 00:32:00
52756	2020-01-01 00:33:00
...	...
53261	2020-01-01 23:59:00

date_merge = pd.merge(df_time, df_date, left_index=True, right_index=True)
date_merge = pd.merge(date_merge, pickd_column_df, left_index=True, right_index=True)

index	longtime_time	longtime_date	value
52755	00:32:00	2020-01-01	23.3
52757	00:34:00	2020-01-01	23.3
52759	00:37:00	2020-01-01	NaN
52760	00:38:00	2020-01-01	NaN
52761	00:39:00	2020-01-01	naN
....	...	...	...
53261	23:59:00	2020-01-01	23.9

now I plot the longtime_date on the x-axis as an example:

ax = date_merge.plot(x ="longtime_date" , y="value" , kind="scatter" ,figsize=[15, 5], linewidth=0.1, alpha=0.6, color="#003399")
plt.show()

it works no error. If I now use longtime_time instead of longtime_date for the x-axis I get the following error message

ax = date_merge.plot(x ="longtime_time" , y="value" , kind="scatter" ,figsize=[15, 5], linewidth=0.1, alpha=0.6, color="#003399")
plt.show()

TypeError: float() argument must be a string or a number, not 'datetime.time'

some further information:

print(date_merge["longtime_time"].dtype)

output:

object

print(date_merge["longtime_date"].dtype)

output:

object

print(date_merge["temperature_ers_lite_1_wermser_0_elsys_0"].dtype)

output:

float64

Answer 1

Ok so I think the issue is you need to convert that column to str.

So at some point before plotting:

date_merge['longtime_time'] = date_merge['longtime_time'].astype(str)
ax = date_merge.plot(x ="longtime_time" , y="value" , kind="scatter" ,figsize=[15, 5], linewidth=0.1, alpha=0.6, color="#003399")
plt.show()

Or could do:

import pandas as pd
import numpy as np
from matplotlib import pyplot as plt
import matplotlib.dates as mdates

date_merge = pd.DataFrame(
[['2020-01-01 00:32:00' ,23.3],
['2020-01-01 00:34:00'      ,23.3],
['2020-01-01 00:37:00'      ,np.nan],
['2020-01-01 00:38:00'      ,np.nan],
['2020-01-01 00:39:00'      ,np.nan],
['2020-01-01 23:59:00'      ,23.9]],
columns = ['longtime'       ,'value'])

date_merge["longtime"] = pd.to_datetime(date_merge["longtime"])

ax = date_merge.plot(x ="longtime" , y="value" , kind="scatter" ,figsize=[15, 5], linewidth=0.1, alpha=0.6, color="#003399")

timeFmt = mdates.DateFormatter('%H:%M:%S')
ax.xaxis.set_major_formatter(timeFmt)
plt.xticks(rotation=90)
plt.show()