<jupyter_start><jupyter_text><jupyter_code>from google.colab import drive
drive.mount('/content/drive')
# import os for file manipulation
import os
# import pandas for tabular or dataframe management
import pandas as pd
# create variable for path to the folder that stores our data
base_path = '/content/drive/My Drive/DWDM_material'
# load data from test.csv to data
data = pd.read_csv(os.path.join(base_path,'test.csv'))
# show head of the data table
data.head()
data.describe()<jupyter_output><empty_output><jupyter_text>Box plot<jupyter_code>from matplotlib import pyplot as plt
plt.boxplot(data['x'])
plt.boxplot(data['x'],vert=False)
plt.boxplot(data['x'],vert=False,whis=1.2)
oput = plt.boxplot(data['x'],vert=False,whis=1.2)
oput['fliers'][0].get_xdata()
oput['whiskers'][0].get_xdata()
oput['whiskers'][1].get_xdata()<jupyter_output><empty_output><jupyter_text>Scatter plot<jupyter_code>plt.scatter(data['x'],data['y'])
plt.scatter(data['x'],data['y'],s=25)
plt.scatter(data['x'],data['y'],s=data['y'])
plt.scatter(data['x'],data['y'],s=data['y'],c='k')
plt.scatter(data['x'],data['y'],s=data['y'],c='r',marker='P')
plt.scatter(data['x'],data['y'],s=data['y'],c='r',marker='P',alpha=0.4)
plt.scatter([44,42,50],[15,14,80],s=250,alpha=0.6)<jupyter_output><empty_output><jupyter_text>HW4 วาดปีกกับนอ ให้ไดโนเสาร์<jupyter_code><jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.20763022743947177, 'fraction_numerical': 0.02127659574468085, 'mean_word_length': 10.658119658119658, 'pattern_counts': {'":': 0, '<': 17, '<?xml version=': 0, '>': 17, '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': '4', 'dir': 'jupyter-structured-clean-dedup', 'id': '471974', 'license': 'MIT', 'n_tokens_mistral': 583, 'n_tokens_neox': 565, 'n_words': 76, 'path': 'Data102.ipynb', 'repo_name': 'tohnperfect/Attention-Gated-Networks', 'size': '1363'}