<jupyter_start><jupyter_text><jupyter_code>from google.colab import files
from google.colab import drive
drive.mount('/content/drive')
import pandas as pd
data= pd.read_csv('/content/drive/MyDrive/Csv /Untitled spreadsheet(csv).csv')
data.head()
data.shape
how_many=data[(data['Asll']>50)]
how_many
len(how_many)
data.groupby(['UNION']).count()['HCO3'].to_frame()
data.groupby(['UNION']).count()['HCO3'].plot()
 data.groupby(['UNION']).count()['HCO3'].plot(kind='bar',figsize=(10,7))
data.HCO3
data.Ca
z=data.iloc[:13:]
z
c=z.sum(axis=1)
z['final index']=c
z
 z['final index']=c
z.to_csv('Untitled spreadsheet(csv).xlsx')
data.groupby(['UNION']).count()['PH'].plot()
 data.groupby(['UNION']).count()['PH'].plot(kind='bar',figsize=(10,7))<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.23598435462842243, 'fraction_numerical': 0.01955671447196871, 'mean_word_length': 8.974025974025974, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 6, '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': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '351722', 'license': 'MIT', 'n_tokens_mistral': 321, 'n_tokens_neox': 310, 'n_words': 39, 'path': 'Water_Quality_python.ipynb', 'repo_name': 'pallapreethi/Palla-Preethi-', 'size': '767'}