Matplotlib/Pandas: Zoom Part of a Plot with Time Series

Question

my task is simple: I have a time series ts (Euro Swiss Franc daily exchange rates between 2010 and 2014) to plot. In that plot I would like to highlight a certa

Answer 1

I have never used pandas, but I think that the problem is the range you are choosing for axins.set_xlim(x1, x2), they seem to be outside of the range. I just used the plotting capabilities of matplotlib and changed the range, and I obtained an image with the zoom.

import numpy as np
import pandas as pd
from matplotlib import pyplot as plt
from mpl_toolkits.axes_grid1.inset_locator import zoomed_inset_axes 
from mpl_toolkits.axes_grid1.inset_locator import mark_inset

# Load the time series
ts = pd.read_csv('EUR_CHF_daily.csv',sep=';', parse_dates=['time'], index_col = 'time',decimal=',')
ts = ts['EUR/CHF']
ts = ts.sort_index(ascending=True)

# Plot
fig = plt.figure(figsize=(14,5))
ax = plt.axes()
ax.plot(ts)

# Label the axis
ax.set_xlabel('')
ax.set_ylabel('EUR/CHF')

#I want to select the x-range for the zoomed region. I have figured it out suitable values
# by trial and error. How can I pass more elegantly the dates as something like
x1 = 1543.90
x2 = 1658.80

# select y-range for zoomed region
y1 = 1.15
y2 = 1.25

# Make the zoom-in plot:
axins = zoomed_inset_axes(ax, 2, loc=1) # zoom = 2
axins.plot(ts)
axins.set_xlim(x1, x2)
axins.set_ylim(y1, y2)
plt.xticks(visible=False)
plt.yticks(visible=False)
mark_inset(ax, axins, loc1=2, loc2=4, fc="none", ec="0.5")
plt.draw()
plt.show()