<jupyter_start><jupyter_text>The data in the csv file was extracted from a [spreadheet](https://collegecost.ed.gov/wwwroot/documents/CATClists2014.xlsx) made available by the [U.S. Department of Education College Affordability and Transparency Center](https://collegecost.ed.gov/).It contains 2014-2015 tuition and fees for universities and colleges in the USA. The data is loaded into the data frame `data`<jupyter_code>data = pd.read_csv("data/college_tuition.csv").set_index("Name of institution")
data.head()
data.dtypes<jupyter_output><empty_output><jupyter_text>Indexing and selection with SeriesFirst we are going to focus on one column in the data frame and extract it into the series `tuition`<jupyter_code>tuition = data["2014-15 Tuition and fees"]
tuition<jupyter_output><empty_output><jupyter_text>- Select the first five entries in the series- Select the last five entries in the series- Select every tenth entry (10% sampling)- What is the tuition of the `'University of Georgia'`?- Select the subseries containing the tuition fees of `'Harvard University'` and `'Massachusetts Institute of Technology'`.- Select the subseries containing tuitions greater than `50000`- Select the subseries containing tuition <= `50000` but greater than `40000`- (Challenge) Select the tuition of institutes of technology, that is colleges with names ending with `Institute of Technology`- (Challenge) What is the cheapest college in `Georgia`? **Hint** you can use the function `sort_values` to sort the series  Indexing and selection with DataFrame<jupyter_code>data.head()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.08364544319600499, 'fraction_numerical': 0.02184769038701623, 'mean_word_length': 6.15625, 'pattern_counts': {'":': 0, '<': 14, '<?xml version=': 0, '>': 13, 'https://': 2, 'lorem ipsum': 0, 'www.': 1, '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': '3', 'dir': 'jupyter-structured-clean-dedup', 'id': '536164', 'license': 'MIT', 'n_tokens_mistral': 481, 'n_tokens_neox': 440, 'n_words': 184, 'path': '15-problem-begin.ipynb', 'repo_name': 'cmw2011/advanced-data-management-and-analytics-spring2021', 'size': '1602'}