Plot is unclear using matplotlib and pandas library

Question

Any explication why I got this kind of plot? The range of index returns is from 100 to 130. I need help to understand this plot above. The code is simple, but the plot is unclear:

#import needed library
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd

#import JPM GBI bound index
df = pd.read_excel('art.xlsx')
df = pd.DataFrame(df) 
df.head(8)

plt.plot(df\['Date'\],df\['Index returns'\])
type(df\['Date'\]\[3\])

Can you clarify what you mean by "unclear"? We don't know anything about the source data for that plot — Nico Haase
– Nico Haase, Commented May 22, 2018 at 8:45
Welcome to SO. I took the liberty to reformat your question a little. Specifically I removed something that did not look like valid Python code, but like a broken link to an image from your code. Can you please verify that everything is still in order? Additionally: What exactly do you expect to happen? What kind of plot would you expect? — m00am
– m00am, Commented May 22, 2018 at 9:14
I think dzejdzej is right. Try to revert y and x axis and see what happens. — el_Rinaldo
– el_Rinaldo, Commented May 22, 2018 at 9:48
i don't think that there is an issue in the data cuz i have Index returns from 100,98,...,130 even when i chnaged the axis nothing changed — Rawia Sammout
– Rawia Sammout, Commented May 22, 2018 at 10:39

ImportanceOfBeingErnest · Accepted Answer · 2018-05-22 12:14:59Z

1

Matplotlib plots the data in the order it is provided. You may sort the data if that is required.

import numpy as np
import matplotlib.pyplot as plt

x = np.array([3, 5, 1, 2, 7, 4, 6, 9, 8])
y = np.array([8, 10, 3, 6, 8, 10, 10, 3, 6])

plt.subplot(121)
plt.plot(x,y, marker="o", label="unsorted")

plt.legend()

# now sort the values
plt.subplot(122)
plt.plot(np.sort(x),y[np.argsort(x)], marker="o", color="C3", label="sorted")

plt.legend()
plt.show()

answered May 22, 2018 at 12:14

ImportanceOfBeingErnest

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1 Comment

Rawia Sammout Over a year ago

Thanks for your clarification it helps

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