exercise-summary-functions-and-maps.ipynb

{"cells":[{"metadata":{},"cell_type":"markdown","source":"**This notebook is an exercise in the [Pandas](https://www.kaggle.com/learn/pandas) course.  You can reference the tutorial at [this link](https://www.kaggle.com/residentmario/summary-functions-and-maps).**\n\n---\n"},{"metadata":{},"cell_type":"markdown","source":"# Introduction\n\nNow you are ready to get a deeper understanding of your data.\n\nRun the following cell to load your data and some utility functions (including code to check your answers)."},{"metadata":{"trusted":true},"cell_type":"code","source":"import pandas as pd\npd.set_option(\"display.max_rows\", 5)\nreviews = pd.read_csv(\"../input/wine-reviews/winemag-data-130k-v2.csv\", index_col=0)\n\nfrom learntools.core import binder; binder.bind(globals())\nfrom learntools.pandas.summary_functions_and_maps import *\nprint(\"Setup complete.\")\n\nreviews.head()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Exercises"},{"metadata":{},"cell_type":"markdown","source":"## 1.\n\nWhat is the median of the `points` column in the `reviews` DataFrame?"},{"metadata":{"trusted":true},"cell_type":"code","source":"median_points =reviews.points.median()\n\n# Check your answer\nq1.check()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#q1.hint()\nq1.solution()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## 2. \nWhat countries are represented in the dataset? (Your answer should not include any duplicates.)"},{"metadata":{"trusted":true},"cell_type":"code","source":"countries =reviews.country.unique()\n\n# Check your answer\nq2.check()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#q2.hint()\nq2.solution()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## 3.\nHow often does each country appear in the dataset? Create a Series `reviews_per_country` mapping countries to the count of reviews of wines from that country."},{"metadata":{"trusted":true},"cell_type":"code","source":"reviews_per_country = reviews.country.value_counts()\n# Check your answer\nq3.check()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#q3.hint()\nq3.solution()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## 4.\nCreate variable `centered_price` containing a version of the `price` column with the mean price subtracted.\n\n(Note: this 'centering' transformation is a common preprocessing step before applying various machine learning algorithms.) "},{"metadata":{"trusted":true},"cell_type":"code","source":"centered_price = reviews.price - reviews.price.mean()\n\n# Check your answer\nq4.check()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#q4.hint()\nq4.solution()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## 5.\nI'm an economical wine buyer. Which wine is the \"best bargain\"? Create a variable `bargain_wine` with the title of the wine with the highest points-to-price ratio in the dataset."},{"metadata":{"trusted":true},"cell_type":"code","source":"bargain_idx = (reviews.points / reviews.price).idxmax()\nbargain_wine = reviews.loc[bargain_idx, 'title']\n# Check your answer\nq5.check()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#q5.hint()\nq5.solution()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## 6.\nThere are only so many words you can use when describing a bottle of wine. Is a wine more likely to be \"tropical\" or \"fruity\"? Create a Series `descriptor_counts` counting how many times each of these two words appears in the `description` column in the dataset."},{"metadata":{"trusted":true},"cell_type":"code","source":"n_trop = reviews.description.map(lambda desc: \"tropical\" in desc).sum()\nn_fruity = reviews.description.map(lambda desc: \"fruity\" in desc).sum()\ndescriptor_counts = pd.Series([n_trop, n_fruity], index=['tropical', 'fruity'])\n\n# Check your answer\nq6.check()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#q6.hint()\nq6.solution()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## 7.\nWe'd like to host these wine reviews on our website, but a rating system ranging from 80 to 100 points is too hard to understand - we'd like to translate them into simple star ratings. A score of 95 or higher counts as 3 stars, a score of at least 85 but less than 95 is 2 stars. Any other score is 1 star.\n\nAlso, the Canadian Vintners Association bought a lot of ads on the site, so any wines from Canada should automatically get 3 stars, regardless of points.\n\nCreate a series `star_ratings` with the number of stars corresponding to each review in the dataset."},{"metadata":{"trusted":true},"cell_type":"code","source":"def stars(row):\n    if row.country == 'Canada':\n        return 3\n    elif row.points >= 95:\n        return 3\n    elif row.points >= 85:\n        return 2\n    else:\n        return 1\nstar_ratings = reviews.apply(stars, axis='columns')\n\n# Check your answer\nq7.check()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#q7.hint()\nq7.solution()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Keep going\nContinue to **[grouping and sorting](https://www.kaggle.com/residentmario/grouping-and-sorting)**."},{"metadata":{},"cell_type":"markdown","source":"---\n\n\n\n\n*Have questions or comments? Visit the [Learn Discussion forum](https://www.kaggle.com/learn-forum/161299) to chat with other Learners.*"}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":4}