How to use map and lambda function to convert a column in pandas to datetime?

Question

I have a column that has time like 9:3:15 (no leading 0s) (3 mins and 15 sec past 9). I would like to plot this (no date, just time) on the x axis. so i tried the following code:

def data_vis(dayN):
    plt.subplots_adjust(bottom=0.2)
    plt.xticks( rotation=25 )
    ax=plt.gca()
    #ax.xaxis_date()
    xfmt = md.DateFormatter('%H:%MM:%S')
    ax.xaxis.set_major_formatter(xfmt)
    plt.plot_date(md.date2num(dayN["Time Stamp"]),dayN["Temperature(deg C)"])
    plt.show()

I got the following error:

DateFormatter found a value of x=0, which is an illegal date; this usually occurs because you have not informed the axis that it is plotting dates, e.g., with ax.xaxis_date()

with ax.xaxis_date() enabled, I got the below error.

'str' object has no attribute 'toordinal'

Since that columns was "str", I thought of using

pd.to_datetime(day2["Time Stamp"], format = '%H:%M:%S)

but it results in the below output:

1900-01-01 09:51:33

Now I would like to try datetime.datetime.strptime using map and/or lambda function for the above said column..

Any help regarding implementation of map function and plotting the data would be really helpful.Also wil the datetime.strptime help in resolving the problem?

thanks,

to clarify: day2["Time Stamp"] has strings representing time, no date. it only holds data within one day, i.e. the date does not change? — FObersteiner
– FObersteiner, Commented May 8, 2020 at 10:19
ok did you try to convert the column day2["Time Stamp"] to datetime (just don't care about the date) and then pass it to plt, without any further conversion? — FObersteiner
– FObersteiner, Commented May 8, 2020 at 13:07
I just tried it and it shows only the H:00:00 in the x-axis ! — Somasundharam Sampath
– Somasundharam Sampath, Commented May 8, 2020 at 13:20

FObersteiner · Accepted Answer · 2020-05-08 13:39:46Z

0

not sure what's going wrong here; the following works fine for me:

import pandas as pd
import numpy as np
from matplotlib import pyplot as plt
import matplotlib.dates as md
# create a dummy df...
dayN = pd.DataFrame({"Temperature(deg C)": np.random.rand(10)+20,
                     "Time Stamp": ['9:3:15','9:3:16','9:3:17','9:3:18','9:3:19',
                                    '9:3:20','9:3:21','9:3:22','9:3:23','9:3:24']})
# format to datetime, don't care about the date:
dayN["Time Stamp"] = pd.to_datetime(dayN["Time Stamp"], format='%H:%M:%S')

plt.subplots_adjust(bottom=0.2)
plt.xticks(rotation=25)
ax = plt.gca()
xfmt = md.DateFormatter('%H:%M:%S')
ax.xaxis.set_major_formatter(xfmt)
plt.plot_date(md.date2num(dayN["Time Stamp"]), dayN["Temperature(deg C)"])
plt.show()

answered May 8, 2020 at 13:39

FObersteiner

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2 Comments

Somasundharam Sampath Over a year ago

I think that because of the no. of entries in my data, matplotlib only shows hourly time like 9:00:00 , 12:00:00 15:00:00. I read it from the comments to the ans here [link]here:stackoverflow.com/a/4091264/12129327 thanks for a solution really appreciate it!

FObersteiner Over a year ago

@SomasundharamSampath: maybe you need to set custom ticks then, see e.g. here or matplotlib docs

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