matplotlib.pyplot x values not displayed as expected

Question

I want the x values to be "yyyy-mm" from 2016-01 to 2020-01 (interval per half year). However, tried many ways the x values still in a mess.
My code is as follows:

import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
import matplotlib.dates as mdates
from pandas.plotting import register_matplotlib_converters
register_matplotlib_converters()

df = pd.read_csv('fcc-forum-pageviews.csv',index_col='date')
df = df[(df['value'] >= df['value'].quantile(0.025)) & (df['value'] <= df['value'].quantile(0.975))]

fig = plt.figure()
fig.set_figwidth(15)
fig.set_figheight(9)
ax = fig.add_subplot(1,1,1)
ax.set_title('Daily freeCodeCamp Forum Page Views 5/2016-12/2019')
ax.set_xlabel('Date')
ax.set_ylabel('Page Views')
ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m'))
ax.plot(df['value'],color='r')

The following is the result:

However, what I expected should be:

The dataset can be downloaded from here.Any help is highly appreciated.

After @r-beginners help, I have updated the code as follows:

import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
import matplotlib.dates as mdates
from pandas.plotting import register_matplotlib_converters
register_matplotlib_converters()

df = pd.read_csv('fcc-forum-pageviews.csv',index_col='date')
df = df[(df['value'] >= df['value'].quantile(0.025)) & (df['value'] <= df['value'].quantile(0.975))]
df.index = pd.to_datetime(df.index)

fig = plt.figure()
fig.set_figwidth(15)
fig.set_figheight(9)
ax = fig.add_subplot(1,1,1)
ax.set_title('Daily freeCodeCamp Forum Page Views 5/2016-12/2019')
ax.set_xlabel('Date')
ax.set_ylabel('Page Views')
ax.set_xticks(range(len(df.index)))
ax.set_xticklabels(range(len(df.index)))
months = mdates.MonthLocator(interval=6)
months_fmt = mdates.DateFormatter('%Y-%m')
ax.xaxis.set_major_locator(months)
ax.xaxis.set_major_formatter(months_fmt)
ax.plot(df['value'], color='r')

now it can display the x values in 6-month interval. However, instead of starting from 2016-07 (the date from the dataframe), it starts from 1970-02. Any hints? Thanks.

r-beginners · Accepted Answer · 2020-08-05 08:55:40Z

2

Convert the date data to pd.to_datetime() You can use MonthLocator to control it. The interval is set to 6 months.

import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
import matplotlib.dates as mdates
from pandas.plotting import register_matplotlib_converters
register_matplotlib_converters()

df = pd.read_csv('fcc-forum-pageviews.csv',index_col='date')
df = df[(df['value'] >= df['value'].quantile(0.025)) & (df['value'] <= df['value'].quantile(0.975))]
df.index = pd.to_datetime(df.index)

fig = plt.figure()
fig.set_figwidth(15)
fig.set_figheight(9)
ax = fig.add_subplot(1,1,1)
ax.set_title('Daily freeCodeCamp Forum Page Views 5/2016-12/2019')
ax.set_xlabel('Date')
ax.set_ylabel('Page Views')
# ax.set_xticks(range(len(df.index)))
# ax.set_xticklabels(range(len(df.index)))
# months = mdates.MonthLocator(interval=6)
# months_fmt = mdates.DateFormatter('%Y-%m')
# ax.xaxis.set_major_locator(months)
# ax.xaxis.set_major_formatter(months_fmt)
ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m'))
ax.plot(df['value'], color='r')

edited Aug 5, 2020 at 8:55

answered Aug 5, 2020 at 5:36

r-beginners

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12 Comments

TinySimonH Over a year ago

Thanks. I can see the interval is 6 months now. However, the starting yyyy-month was 1970-02 instead of the year-month from the dataframe (should be 2016-07). Do you know why? What is wrong with ax.plot(df.index, df['value'], color='r')? seems the x values was not starting from the date in the dataset

r-beginners Over a year ago

I suspect this may be the cause of the problem, but even after dealing with it, it didn't get it right. Are you also 'matplotlib:3.3.0'?

TinySimonH Over a year ago

Yes, the version is 'matplotlib:3.3.0'

r-beginners Over a year ago

The cause was elsewhere. The dates were not in chronological form. Fixed the code.

r-beginners Over a year ago

You can do this simply by converting the next date/time format to pd.to_datetime() in your original code.

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Vishesh Mangla · Accepted Answer · 2020-08-05 04:37:46Z

0

Please read on Xticks

From the docs

>>> locs, labels = xticks()  # Get the current locations and labels.
>>> xticks(np.arange(0, 1, step=0.2))  # Set label locations.
>>> xticks(np.arange(3), ['Tom', 'Dick', 'Sue'])  # Set text labels.
>>> xticks([0, 1, 2], ['January', 'February', 'March'],
...        rotation=20)  # Set text labels and properties.
>>> xticks([])  # Disable xticks.

answered Aug 5, 2020 at 4:37

Vishesh Mangla

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