<jupyter_start><jupyter_text><jupyter_code>import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
path="https://raw.githubusercontent.com/KhushbooSingh17/18CSE140/main/governors_county.csv"
import pandas as pd
data=pd.read_csv(path)
data
data.head()
data.tail()
data.dropna(axis=0,inplace=True)
data.shape
data.head()
plt.scatter(data['current_votes'],data['total_votes'],c='red')
plt.xlabel('current_votes')
plt.ylabel('total_votes')
plt.show()

plt.hist(data['current_votes'])
plt.show()
plt.hist(data['current_votes'])
plt.hist(data['current_votes'],color='orange',edgecolor='white',bins=5)
plt.title=("histogram of kilometer")
plt.xlabel("current_votes")
plt.ylabel("total_votes")
plt.show()
import seaborn as sns
sns.set(style='darkgrid')
sns.regplot(x=data['current_votes'],y=data['total_votes'])
sns.set(style='darkgrid')
sns.regplot(x=data['current_votes'],y=data['total_votes'],marker='*',fit_reg=False)
sns.distplot(data['current_votes'])
sns.displot(data['current_votes'],kde=False) 
sns.distplot(data['current_votes'],kde=False,bins=5)
sns.countplot(x="state",data=data)
sns.countplot(x="state",data=data)
sns.boxplot(y=data['percent'])
sns.boxplot(x=data['current_votes'],y=data['total_votes'],data=data,hue='percent')<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.19107282693813626, 'fraction_numerical': 0.007830853563038372, 'mean_word_length': 12.595744680851064, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, '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': '459200', 'license': 'Apache-2.0', 'n_tokens_mistral': 533, 'n_tokens_neox': 511, 'n_words': 53, 'path': 'Assignment3.ipynb', 'repo_name': 'KhushbooSingh17/18CSE140', 'size': '1277'}