<jupyter_start><jupyter_text>**Profiling a dataframe**<jupyter_code>from google.colab import files
uploaded = files.upload()
import pandas as pd

# Import the dataframe
eq = pd.read_csv('Earthquake_database.csv')

# Describe the dataframe
eq.describe()
!pip install --upgrade pandas_profiling
import pandas_profiling
pandas_profiling.__version__
# Import the pandas profiling package
from pandas_profiling import ProfileReport

# Get the pandas profiling report
eq.profile_report()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.07827788649706457, 'fraction_numerical': 0.0, 'mean_word_length': 7.39344262295082, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, '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': '488713', 'license': 'MIT', 'n_tokens_mistral': 173, 'n_tokens_neox': 156, 'n_words': 43, 'path': 'Profiling a dataframe.ipynb', 'repo_name': 'thirasit/Advanced-Forecasting-Model', 'size': '511'}