<jupyter_start><jupyter_text>Import librarys<jupyter_code>import pandas as pd 
import matplotlib.pyplot as plt
import numpy as np<jupyter_output><empty_output><jupyter_text>Importing data set as pandas DataFrame<jupyter_code>dataset=pd.read_csv('iris_dataset.csv')
dataset.head()<jupyter_output><empty_output><jupyter_text>Converting DataFrame to numpy arrays<jupyter_code>ds=dataset.to_numpy()
sepal_length_field=ds[:,0]
sepal_width_field=ds[:,1]
median_sl=np.median(sepal_length_field)
print('median of the sepal width filed is: ',median_sl)
median_sw=np.median(sepal_width_field)
std_sw=np.std(sepal_width_field)
print('median of the sepal width filed is: ',median_sw)
print('standrd deviation of the sepal width filed is: ',std_sw)<jupyter_output>median of the sepal width filed is:  3.0
standrd deviation of the sepal width filed is:  0.43441096773549437<jupyter_text>Percentile of the field Percentiles are used in statistics to give you a number that describes the value that a given percent of the values are lower than.<jupyter_code>petal_length_field=ds[:,2]
petal_width_field=ds[:,3]
per_pl=np.percentile(petal_length_field,50)
print(f'petal lenght are lower than {per_pl}')<jupyter_output>petal lenght are lower than 4.35<jupyter_text>Ploting histogram<jupyter_code>plt.hist(petal_length_field)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.09206586826347306, 'fraction_numerical': 0.021706586826347306, 'mean_word_length': 9.527559055118111, 'pattern_counts': {'":': 0, '<': 19, '<?xml version=': 0, '>': 19, 'https://': 0, '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': '5', 'dir': 'jupyter-structured-clean-dedup', 'id': '512858', 'license': 'Apache-2.0', 'n_tokens_mistral': 511, 'n_tokens_neox': 481, 'n_words': 110, 'path': 'ML_Basic_iris_dataset_02.ipynb', 'repo_name': 'arianAsg/machin_learning_basics', 'size': '1336'}