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how do we plot a scatter plot for time in python

i want to plot a scatter plot between mentioned two columns k and s . k should be on x axis showing time on hourly basis for 24 hours and s should be on y axis. i have already tried some code using using sns.relplot but got attribute error.
data columns in which we want scatter plot
code which we tried with error

Try:
import matplotlib.dates as mdates
from datetime import time
import matplotlib.pyplot as plt
import pandas as pd
df = pd.DataFrame([['2020-05-26 06:15:07','105'], ['2020-05-26 06:15:07','41'], ['2020-05-26 06:16:51','95']], columns=["k", "s"])
df.k = pd.to_datetime(df.k, format='%Y-%m-%d %H:%M:%S')
ax = sns.scatterplot(df.k, df.s)
ax.xaxis.set_major_formatter(mdates.DateFormatter("%Y-%m-%d %H:%M:%S"))
ax.tick_params(axis="x", rotation=45)
ax.plot()
import matplotlib.dates as mdates
from datetime import time
import matplotlib.pyplot as plt
df = pd.DataFrame([['2020-05-26 06:15:07','105'], ['2020-05-26 06:15:07','41'], ['2020-05-26 06:16:51','95']], columns=["k", "s"])
df.k = pd.to_datetime(df.k, format='%Y-%m-%d %H:%M:%S')
df.set_index(['k'],inplace=True)
ax = sns.scatterplot(df.index, df.s)
# ax.set(xlabel="time", ylabel="values")
ax.set_xlim(df.index[0], df.index[-1])
ax.xaxis.set_major_locator(mdates.HourLocator())
ax.xaxis.set_major_formatter(mdates.DateFormatter("%Y-%m-%d %H:%M:%S"))
ax.tick_params(axis="x", rotation=45)
ax.plot()

matplotlib to show x-axis with custom date formats and interval

Using matplotlib and mpl_finance to plot candlesticks. Data is in csv AAPL.
I want to show the x-axis as year and month only, i.e."yyyy-mmm", so:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from mpl_finance import candlestick2_ohlc
import matplotlib.dates as mdates
data = pd.read_csv('C:\\AAPL.csv', delimiter = "\t")
data = data.sort_values(['Date'], ascending=True)
data = data.tail(100)
fig = plt.figure(figsize=(6,4))
plt.ylim(60, 200)
ax1 = fig.add_subplot(111)
cl =candlestick2_ohlc(ax=ax1,opens=data['Open'],highs=data['High'],lows=data['Low'],closes=data['Close'],width=0.6)
ax1.set_xticks(np.arange(len(data)))
ax1.set_xticklabels(data['Date'], fontsize=10, rotation=90)
# every month of the year like 2008-Jan, 2008-Feb...
locator = mdates.MonthLocator()
fmt = mdates.DateFormatter('%Y-%b')
X = plt.gca().xaxis
X.set_major_locator(locator)
X.set_major_formatter(fmt)
plt.show()
It doesn't show anything.
Also tried below but doesn't work neither:
plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%m/%d/%Y'))
plt.gca().xaxis.set_major_locator(mdates.DayLocator())
How can I have the x-axis only show the year and month??
Thank you.

Try following solution,
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from mpl_finance import candlestick_ohlc
import matplotlib.dates as mdates
data = pd.read_csv('C:\AAPL.csv')
data = data.sort_values(['Date'], ascending=True)
data = data.tail(100)
from matplotlib.dates import date2num, DayLocator, DateFormatter
data['Date'] = date2num(pd.to_datetime(data['Date']).tolist())
fig, ax=plt.subplots(figsize=(10, 10))
candlestick_ohlc(ax, data.as_matrix(),width=0.6)
ax.set(xlabel='AAPL')
ax.xaxis.set_major_locator(DayLocator())
ax.xaxis.set_major_formatter(DateFormatter('%Y-%b'))
ax.xaxis.set_major_locator(mdates.WeekdayLocator(interval=4))
plt.show()
Note: I have used candlestick_ohlc instead of candlestick2_ohlc.
Output :

Why am I not able to get proper dates in my graph?

I am not able to get the dates in correct form in my output.It is concerned with plottng of 3 stock data (opening price) for 4 days on single axis.
My code is
# Import matplotlib.pyplot
import matplotlib.pyplot as plt
from datetime import date
from nsepy import get_history
avenue_df=get_history(symbol='DMART',start=date(2018,5,6),end=date(2018,5,10))
avenue_df.Open.plot(color='green', label='DMART')
shriram_df = get_history(symbol='SRTRANSFIN',start=date(2018,5,6),end=date(2018,5,10))
shriram_df.Open.plot(color='red', label='SHRI')
infy_df = get_history(symbol='INFY',start=date(2018,5,6),end=date(2018,5,10))
infy_df.Open.plot(color='blue', label='INFY')
# Add a legend in the top left corner of the plot
plt.legend(loc='upper left')
# Display the plot
plt.show()
My output is

You can use the DayLocator and DateFormatter from matplotlib.dates
import matplotlib.pyplot as plt
from datetime import date
from nsepy import get_history
avenue_df=get_history(symbol='DMART',start=date(2018,5,6),end=date(2018,5,10))
avenue_df.Open.plot(color='green', label='DMART')
shriram_df = get_history(symbol='SRTRANSFIN',start=date(2018,5,6),end=date(2018,5,10))
shriram_df.Open.plot(color='red', label='SHRI')
infy_df = get_history(symbol='INFY',start=date(2018,5,6),end=date(2018,5,10))
ax = infy_df.Open.plot(color='blue', label='INFY')
# Add a legend in the top left corner of the plot
plt.legend(loc='upper left')
# Display the plot
#Format the xaxis date
from matplotlib.dates import DateFormatter, DayLocator
ax.xaxis.set_major_locator(DayLocator())
ax.xaxis.set_major_formatter(DateFormatter('%Y/%m/%d'))
plt.show()

matplotlib uppercase tick labels

I'm trying to set the x-axis tick label in matplotlib (2.1.0) (Python 3.6.3 | Windows 10) to uppercase by adding the pattern with the flag %^b like this (plot code):
ax.xaxis.set_minor_formatter(mdates.DateFormatter('%^b'))
However I'm getting the error
ValueError: Invalid format string
With %b I get the plot without any error:
Additionally, I'd like to remove the first and last tick labels to avoid the repetition.
I wonder if you know any workaround for my problem.

In python a string is converted to upper case via str.upper(). You may apply this via a matplotlib.ticker.FuncFormatter to the labels produced via the DateFormatter
fmt= lambda x,pos: mdates.DateFormatter('%b')(x,pos).upper()
ax.xaxis.set_major_formatter(ticker.FuncFormatter(fmt))
Complete example:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import matplotlib.ticker as ticker
x = pd.date_range("2001-01-01", "2001-12-31", freq="5D")
y = np.random.rand(len(x))
fig, ax=plt.subplots()
ax.plot(x,y)
ax.xaxis.set_major_locator(mdates.MonthLocator())
fmt= lambda x,pos: mdates.DateFormatter('%b')(x,pos).upper()
ax.xaxis.set_major_formatter(ticker.FuncFormatter(fmt))
plt.show()

Editing the date formatting of x-axis tick labels

I am looking to edit the formatting of the dates on the x-axis. The picture below shows how they appear on my bar graph by default. I would like to remove the repetition of 'Dec' and '2012' and just have the actual date numbers along the x-axis.
Any suggestions as to how I can do this?

In short:
import matplotlib.dates as mdates
myFmt = mdates.DateFormatter('%d')
ax.xaxis.set_major_formatter(myFmt)
Many examples on the matplotlib website. The one I most commonly use is here

While the answer given by Paul H shows the essential part, it is not a complete example. On the other hand the matplotlib example seems rather complicated and does not show how to use days.
So for everyone in need here is a full working example:
from datetime import datetime
import matplotlib.pyplot as plt
from matplotlib.dates import DateFormatter
myDates = [datetime(2012,1,i+3) for i in range(10)]
myValues = [5,6,4,3,7,8,1,2,5,4]
fig, ax = plt.subplots()
ax.plot(myDates,myValues)
myFmt = DateFormatter("%d")
ax.xaxis.set_major_formatter(myFmt)
## Rotate date labels automatically
fig.autofmt_xdate()
plt.show()

From the package matplotlib.dates as shown in this example the date format can be applied to the axis label and ticks for plot.
Below I have given an example for labeling axis ticks for multiplots
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import pandas as pd
df = pd.read_csv('US_temp.csv')
plt.plot(df['Date'],df_f['MINT'],label='Min Temp.')
plt.plot(df['Date'],df_f['MAXT'],label='Max Temp.')
plt.legend()
####### Use the below functions #######
dtFmt = mdates.DateFormatter('%b') # define the formatting
plt.gca().xaxis.set_major_formatter(dtFmt) # apply the format to the desired axis
plt.show()
As simple as that

This wokrs prfectly for me
import matplotlib.pyplot as plt
from matplotlib.ticker import (MultipleLocator, FormatStrFormatter,
AutoMinorLocator)
import matplotlib.dates as mdates
dtFmt = mdates.DateFormatter('%Y-%b') # define the formatting
plt.gca().xaxis.set_major_formatter(dtFmt)
# show every 12th tick on x axes
plt.gca().xaxis.set_major_locator(mdates.MonthLocator(interval=1))
plt.xticks(rotation=90, fontweight='light', fontsize='x-small',)