<jupyter_start><jupyter_text>Discriptive Statistics : Mean, Median, Mode  Import Libraries<jupyter_code>import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns<jupyter_output><empty_output><jupyter_text>Read the data<jupyter_code>data_frame = pd.read_csv("Data.csv")
data_frame.info()
data_frame
data_frame['Los Angeles'] = pd.to_numeric(data_frame['Los Angeles'], errors='coerce')
data_frame<jupyter_output><empty_output><jupyter_text>Mean<jupyter_code>data_frame['New York City'].mean()
data_frame['Los Angeles'].mean()<jupyter_output><empty_output><jupyter_text>Median<jupyter_code>data_frame.describe()
data_frame.describe().loc['50%']
data_frame.median()
data_frame.median()[0]<jupyter_output><empty_output><jupyter_text>Mode<jupyter_code>data_frame.mode()
data_frame.describe()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.13176470588235295, 'fraction_numerical': 0.0035294117647058825, 'mean_word_length': 13.423728813559322, 'pattern_counts': {'":': 0, '<': 21, '<?xml version=': 0, '>': 21, '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': '401802', 'license': 'MIT', 'n_tokens_mistral': 324, 'n_tokens_neox': 313, 'n_words': 41, 'path': 'Mean Median Mode Lesson.ipynb', 'repo_name': 'Ishaan28malik/DM-ML', 'size': '850'}