<jupyter_start><jupyter_text>Script for reading data for Problem 5.1 (data_AlgaeGrowth.txt) in Applied Statistics 2021 exam:This script reads the file __"data_AlgaeGrowth.txt"__ for Problem 5.1 in the exam of Applied Statistics 2021/22. This data files contains 90 entries in three columns: * **time** (hours) of measurement,* **area** ($\mathrm{cm}^2$) of the algae coverage,* **area uncertainty** ($\mathrm{cm}^2$).The script was distributed along with the exam and the data file itself on the 20th of January 2022.  Author: - <NAME> (<NAME>, <EMAIL>)  Date:    - 19th of January 2022 (first version)<jupyter_code>import pandas as pd
dataframe = pd.read_csv('data_AlgaeGrowth.csv', header=0, index_col=None)
time, area, err_area = dataframe.values.T
dataframe<jupyter_output><empty_output><jupyter_text>Print the first 10 entries to check the content of the file:<jupyter_code>for i in range(10):
    print(f"  time = {time[i]:4.2f} hrs    area = {area[i]:6.2f} cm2    err_area = {err_area[i]:5.2f} cm2")<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.12258687258687259, 'fraction_numerical': 0.041505791505791506, 'mean_word_length': 5.563291139240507, 'pattern_counts': {'":': 0, '<': 12, '<?xml version=': 0, '>': 12, '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': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '626438', 'license': 'MIT', 'n_tokens_mistral': 383, 'n_tokens_neox': 341, 'n_words': 115, 'path': 'AppStat2022/DataAndCodeForExam/DataReader_Problem5.1_AlgaeGrowth.ipynb', 'repo_name': 'EiriniNBI/eirinipy', 'size': '1067'}