Create a line chart with datetime on x-axis and number of records on y-axis

Question

I am trying to create a line chart with only the month-year part from the datetime data on the x-axis and the number of records for each month on the y.

So far, I have copied the two columns that I need from the original dataframe into a new one and changed the format of the datetime column:

line_chart =frame[['index', 'Start Time and Date']].copy()
line_chart['Start Time and Date']=line_chart['Start Time and Date'].dt.to_period('M')

Next, I tried to use plotly to create the chart:

import plotly.express as px
fig = px.line(line_chart, x='Start Time and Date', y='index')
fig.show()

But I get this error: Object of type Period is not JSON serializable

I also tried plotting with matplotlib :

x=line_chart['Start Time and Date']
y=line_chart['index']
plt.plot(x,y)
plt.gcf().autofmt_xdate()

plt.show()

But again error: `view limit minimum 0.0 is less than 1 and is an invalid Matplotlib date value. This often happens if you pass a non-datetime value to an axis that has datetime units

Here are some screenshots of the data: Frame Frame1

I would really appreciate some help! Thank you!

Answer 1

If you leave the format of the 'Start Time and Date' column unchanged to the default pandas datetime format and instead update the format of the x-axis tick labels your code should work.

import pandas as pd

frame = pd.DataFrame({'Start Time and Date': ['2013-07-01 00:00:00', '2013-07-01 00:00:02', '2013-07-01 00:01:04',
                                              '2013-07-01 00:01:06', '2013-07-01 00:01:10', '2013-08-01 00:00:00',
                                              '2013-08-01 00:00:02', '2013-09-01 00:01:04', '2013-09-01 00:01:06',
                                              '2013-10-01 00:01:10', '2013-10-01 00:02:10', '2013-11-01 00:03:10',
                                              '2013-12-01 00:03:10', '2013-12-02 00:04:10', '2013-12-03 00:05:10'],
                      'index': [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]})

# Number of records per month
line_chart = frame.copy()
line_chart.index = pd.DatetimeIndex(line_chart['Start Time and Date'])
line_chart = pd.DataFrame(line_chart.resample('M')['index'].count())
line_chart.reset_index(inplace=True)

# Plotly
import plotly.express as px

fig = px.line(line_chart, x='Start Time and Date', y='index')
fig.update_layout(xaxis=dict(tickformat='%m-%Y'))
fig.show()

# Matplotlib
import matplotlib.pyplot as plt
import matplotlib.dates as mdates

x = line_chart['Start Time and Date']
y = line_chart['index']

fig, ax = plt.subplots(figsize=(10, 6))
plt.plot(x, y)
ax.xaxis.set_major_locator(mdates.MonthLocator())
ax.xaxis.set_major_formatter(mdates.DateFormatter('%m-%Y'))
plt.show()