<jupyter_start><jupyter_text>Importing the libraries<jupyter_code>import pandas as pd
data = pd.read_csv('data.csv', header=0, index_col= 0)
#dataset
data.head()
from matplotlib import pyplot
#show the dataset
data.plot()
#importing acf and pacf
from statsmodels.graphics.tsaplots import plot_acf
from statsmodels.graphics.tsaplots import plot_pacf
plot_acf(data)
plot_pacf(data)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.09290953545232274, 'fraction_numerical': 0.004889975550122249, 'mean_word_length': 8.318181818181818, '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': '348391', 'license': 'MIT', 'n_tokens_mistral': 154, 'n_tokens_neox': 146, 'n_words': 35, 'path': 'ACF & PACF/ACF and PACF.ipynb', 'repo_name': 'AmitHasanShuvo/Time-Series-Analysis', 'size': '409'}