Pandas dataframe plot(): x-axis date labels display but not data

I am trying to plot data as a function of time (years) from a pandas data frame. A summary of the data is shown here:

           DATE    WALCL
0    2010-08-18  2313662
1    2010-08-25  2301015
2    2010-09-01  2301996
3    2010-09-08  2305802
4    2010-09-15  2296079
517  2020-07-15  6958604
518  2020-07-22  6964755
519  2020-07-29  6949032
520  2020-08-05  6945237
521  2020-08-12  6957277

I try to plot the data using the following code:

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

years = mdates.YearLocator()   # every year
months = mdates.MonthLocator()  # every month
years_fmt = mdates.DateFormatter('%Y')

dfData = pd.read_csv(sPathIn+sFname, skiprows = 0)

ax = dfData.plot()
ax.xaxis.set_major_locator(years)
ax.xaxis.set_major_formatter(years_fmt)
ax.xaxis.set_minor_locator(months)
datemin = np.datetime64(dfData['DATE'][0], 'Y')
datemax = np.datetime64(dfData['DATE'].iloc[-1], 'Y') + np.timedelta64(1, 'Y')
ax.set_xlim( datemin, datemax)     
plt.show()

When I run this code, the plot axes are displayed correctly but the time series data (WALCL) does not appear.

If I omit ax.set_xlim( datemin, datemax), the time series data are shown, but the x-axis is no longer formatted correctly (starts at 1970 and runs until 1971).

Here is a modified code example:

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

years = mdates.YearLocator()   # every year
months = mdates.MonthLocator()  # every month
years_fmt = mdates.DateFormatter('%Y')

sPathIn = "C:\\Users\\reg\\projects\\notes\\Political_Economy\\S&P+Fed-Assets\\"
sFname = "WALCL.csv"

and here is the traceback:

Traceback (most recent call last):

  File "C:\Users\reg\projects\Notes\Political_Economy\S&P+Fed-Assets\Python\s&p-fed-assets-v0.2.3.py", line 25, in <module>
    dfData.set_index('DATE', inplace=True)

  File "C:\Users\reg\Anaconda3\lib\site-packages\pandas\core\frame.py", line 4545, in set_index
    raise KeyError(f"None of {missing} are in the columns")

KeyError: "None of ['DATE'] are in the columns"

    # load data
    dfData = pd.read_csv(sPathIn+sFname, skiprows = 0, parse_dates=['DATE'], index_col='DATE')
    
    #set up plot fxn
    dfData.set_index('DATE', inplace=True)
    ax = dfData.plot('DATE', 'WALCL')
    
    # format the ticks
    ax.xaxis.set_major_locator(years)
    ax.xaxis.set_major_formatter(years_fmt)
    ax.xaxis.set_minor_locator(months)
    
    datemin = np.datetime64(dfData['DATE'][0], 'Y')
    datemax = np.datetime64(dfData['DATE'].iloc[-1], 'Y') + np.timedelta64(1, 'Y')
    ax.set_xlim( datemin, datemax)   
    plt.show()

• Dataset is at Assets: Total Assets: Total Assets (Less Eliminations from Consolidation): Wednesday Level (WALCL)
• Verify the DATE column is in a datetime format by using parse_dates with .read_csv.

Set DATE as the index

import pandas as pd
import numpy as np

# verify the DATE column is in a datetime format and set it as the index
dfData = pd.read_csv('WALCL.csv', skiprows=0, parse_dates=['DATE'], index_col='DATE')

# plot the data
ax = dfData.plot(figsize=(20, 8))

datemin = np.datetime64(dfData.index.min(), 'Y')
datemax = np.datetime64(dfData.index.max(), 'Y') + np.timedelta64(1, 'Y')
ax.set_xlim(datemin, datemax)

Leave DATE as a column

import pandas as pd

# read file
dfData = pd.read_csv('WALCL.csv', skiprows=0, parse_dates=['DATE'])

# plot data
ax = dfData.plot('DATE', 'WALCL', figsize=(20, 8))