I have the following code/output:
import pandas as pd
import numpy as np
%matplotlib inline
import matplotlib.pyplot as plt
from IPython.core.pylabtools import figsize
figsize(16, 7)
from fredapi import Fred
fred = Fred(api_key = “3ae9356118b31ee7ff5fa03f49c0d6f6”)
df = fred.get_series(“ICERATES1100USD2Y”).tail(250)
ret = df.pct_change()
ret = ret.dropna()
#export_excel = ret.to_excel (r’C:\Users\Mark\Documents\Python\export_6040.xlsx’, index=True, header=True)
Histogram + distribution of returns
from scipy.stats import norm, t, jarque_bera
from statsmodels.tsa.stattools import adfuller as adf
from statsmodels.stats.diagnostic import het_breushpagan as bp
from statsmodels.tsa.stattools import acf
from statsmodels.tsa.stattools import pacf
import seaborn as sns
ax = sns.distplot(ret, fit=norm, kde=False, rug=True)
plt.title(‘2yr USD Swap Rate - Distribution of Daily Returns’)
plt.xlabel(‘Return (%)’)
plt.ylabel(‘Instances’);
print(‘STATISTICS:’)
print('Sample size: ', len(ret))
print('Mean: ', ret.mean())
print('Variance: ', ret.std())
print('Skew: ', ret.skew())
print('Kurtosis: ', ret.kurt())
print('Maximum: ', ret.max())
print('Minimum: ', ret.min())
print(‘Jarque-Bera Test Results:’, jarque_bera(ret))
print(‘Augmented Dickey-Fuller Test Results:’, adf(ret, maxlag=1)[0:2])
print(‘Autocorrelation:’, acf(ret, nlags=5))
print(‘Partial-Autocorrelation:’, pacf(ret, nlags=5))
Output:
Any ideas on how to highlight the last data-point with a red line??? Thx 