Shifting Start Position Of X Axis Of Line Chart

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1 Shifting start position of X Axis of line chart

Problem Description:

I want to shift the start position of the red line from "FEB-2020" to "JAN-2021". Currently this is my code and a picture of my current output. Basically Shorten the period of the whole graph to the dates stated above.

# plot daily vaccinated
fig, ax1= plt.subplots(1,figsize=(20,10))
# set up
plt.ticklabel_format(style='plain') #changing the tick figure from le 6 to millions
plt.setp(ax1, xticks= np.arange(0, 680, 30), xticklabels=vac_dates)
# plot chart
ax1.plot(vaccinated['received_at_least_one_dose'], label= 'Total Vaccinated', c='Red')
# axis and legend settings
ax1.set_ylabel('population (millions)', size= 14)
ax1.set_title('Monthly Vaccinated Numbers', size= 20)
plt.xticks(rotation=45)
plt.grid()

ax1.legend(loc="upper left")
##########################################################
# plot daily covid cases
ax2 = ax1.twinx()

# np.arrange looks at the number of rows
plt.setp(ax2, xticks= np.arange(0, 1035, 31), xticklabels=dates)
ax2.xaxis.tick_top()
ax2.plot(infected_update)

plt.xlabel('date', fontsize=14)
plt.ylabel('population (thousands)', fontsize=14)
 
plt.grid(False)

ax2.legend(['imported','local'], loc="upper right")

Output from code

I’ve tried using codes from the following links but it doesn’t seem to work

https://stackoverflow.com/questions/29370057/select-dataframe-rows-between-two-dates

https://stackoverflow.com/questions/32434607/how-to-shift-a-graph-along-the-x-axis

Solution – 1

Here is a very basic example using pandas, datetime index and matplotlib altogether. It is important to make sure the index is of type DatetimeIndex.

import pandas as pd
import matplotlib.pyplot as plt

df = pd.DataFrame({'a':[3,4,5]}, index=pd.date_range('2020-01-03', '2020-01-05', freq='D'))
df_2 = pd.DataFrame({'b':[1,2,3,4,5], 'c':[1,2,2,2,2]}, index=pd.date_range('2020-01-01', '2020-01-05', freq='D'))

# plot daily vaccinated
fig, ax1= plt.subplots(1,figsize=(10,5))
# set up
ax1.plot(df.index, df['a'], label= 'Total Vaccinated', c='Red')
# axis and legend settings
ax1.set_ylabel('population (millions)', size= 14)
ax1.set_title('Monthly Vaccinated Numbers', size= 20)
plt.xticks(rotation=45)
plt.grid()

ax1.legend(loc="upper left")

##########################################################
# plot daily covid cases
ax2 = ax1.twinx()

# np.arrange looks at the number of rows
ax2.xaxis.tick_top()
ax2.plot(df_2.index, df_2['b'], color='Orange')

plt.xlabel('date', fontsize=14)
plt.ylabel('population (thousands)', fontsize=14)

plt.grid(False)

This means in your case, you have to make sure to set parse_dates=True and set the index, when your read your data. Using pd.read_csv() this could look like

df = pd.read_csv('covid.csv', sep=',', parse_dates=True, index_col=0)

Because you have to DataFrames, you have so make yure both have a DatetimeIndex. Afterwards just replace the columns in the two calls with ac.plot().

Comment:

If you want to plot all columns of a Dataframe, ax2.plot(df_2.index, df_2) works. If your want to select a subset of columns ax2.plot(df_2.index, df_2[['b', 'c']]) is doing the job.

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