DateFormatter is bringing 1970 as year not the original year in the dataset

Question

I am trying to plot time series data. But x axis ticks are not coming the way it should. I wanted to out mont and year as x axis ticks. here is my code

from matplotlib.dates import DateFormatter
import matplotlib.dates as mdates
fig,ax = plt.subplots()
df_month.loc['2017', "Volume"].plot.bar(color='blue', ax=ax)
ax.set_ylabel("Volume")
ax.set_title("Volume")
date_form = DateFormatter("%y-%m")
ax.xaxis.set_major_formatter(date_form)

plt.xticks(rotation=45)
plt.show()

The output looks like this What am I doing wrong? Please help.

My dataset looks like this:

Here is df_month data:

Answer 1

I was having the same issue. The solution is really contained in the answer from @Ruthger Righart which I had trouble understanding at first, but the key change is using matplotlib pyplot plotting instead of the pandas plotting as mentioned here and in the link in the comments mentioned by @Trenton McKinney. First filter the data to the years you want to plot then call the plot like @Ruthger Righart did:

import matplotlib.pyplot as plt
fig,ax = plt.subplots()
ax.bar(df_month['Date'], df_month['Volume'])

Add the labels as you did originally.

Answer 2

The following gives the right x-axis labels.

Import modules

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

Example data

df_month = pd.DataFrame({'Date':['2006-01-03', '2006-02-04', '2006-02-08'], 'Volume':[24232729, 20553479, 20500000]}) # '2006-01-03', '2006-01-04'

df_month['Date'] = pd.to_datetime(df_month['Date'])

Plotting

fig,ax = plt.subplots()
ax.set_ylabel("Volume")
ax.set_title("Volume")

ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m'))
ax.bar(df_month['Date'], df_month['Volume'])

plt.xticks(df_month['Date'], rotation=90)
plt.show()