<jupyter_start><jupyter_text><jupyter_code>import numpy as np
import pandas as pd

import matplotlib.pyplot as plt
import seaborn as sns

url='https://raw.githubusercontent.com/Srinunosina/FDS/master/currencies.csv?token=<KEY>'
df = pd.read_csv(url, index_col=0)
print(df.head(5))
df1 = pd.DataFrame(df, columns = ['Euro', 'Japanese Yen', 'U.K. Pound Sterling','U.S. Dollar', 'Australian Dollar', 'Indian Rupee','Chinese Yuan'])
df1.tail(5)
#Euro, Japanese Yen, U.K. Pound Sterling, US Dollar, Australian Dollar, Indian Rupee.
df1.corr()
df1.corr(method='kendall')
fig, ax = plt.subplots(figsize=(10,10))
corr = df1[["Indian Rupee", "Australian Dollar", "U.S. Dollar", "Japanese Yen", "Euro"]].corr()
sns.heatmap(corr, xticklabels=corr.columns.values, yticklabels=corr.columns.values, annot=True, ax=ax)
plt.show()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.16943127962085308, 'fraction_numerical': 0.014218009478672985, 'mean_word_length': 6.681818181818182, 'pattern_counts': {'":': 0, '<': 6, '<?xml version=': 0, '>': 6, 'https://': 1, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '158553', 'license': 'Apache-2.0', 'n_tokens_mistral': 356, 'n_tokens_neox': 318, 'n_words': 70, 'path': 'BivariateAnalysis_Magrix.ipynb', 'repo_name': 'Srinunosina/npoi', 'size': '868'}