{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Visualization" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Replicate a plot" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Your predeccessor has created the graph shown below for some publication. Since then things have changed and you need to reproduce the plot with new data. However, the code that produced it was lost (it only ever existed in an interactive `ipython` session, the computer on which it was run has long been replaced). In addition the person who created the plot is no longer in academia and cannot be reached.\n", "\n", "From looking at the plot you notice multiple features:\n", "\n", "\n", "- There are two subplots (`plt.subplot` or `plt.subplots`?). The lower one is smaller (`gridspec`) and the two subplots share an $x$-axis.\n", "- The top subplot shows both the PDF and a normalized histogram of $N = 1000$ randomly generated values of (presumably) a normal distribution (`scipy.stats.norm`). It has a meaningful title.\n", "- The top plot also contains the corresponding CDF on a separate y-axis (`ax.twinx`). It is a different color than the other plots.\n", "- The second plot contains the residual between the PDF and the histogram, using `plt.step` in order to match the binning of the histogram.\n", "- The overall plot style is not the default one. Hopefully a preset style was used. The top plot contains a grid matching the right $y$-axis and the bottom plot has a grid matching both the $x$- and $y$-axis.\n", "- In addition, the number of events is added to the plot (`plt.text`) as well as a `plt.legend` in the upper left corner, which even has a `title` It only contains the label for the histogram and the PDF.\n", "- The axis are all properly labeled. The $x$-axis even has a fancy \\LaTeX label.\n", "\n", "Try to replicate the plot as closely as possible." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "![](plot_replication.png)" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "ExecuteTime": { "end_time": "2020-06-26T14:39:39.955120Z", "start_time": "2020-06-26T14:39:38.031868Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from scipy import stats\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "\n", "np.random.seed(13)\n", "\n", "gauss = stats.norm(loc=0, scale=1)\n", "x = np.linspace(-5, 5)\n", "pdf_values = gauss.pdf(x)\n", "generated = gauss.rvs(1000)\n", "hist, bins = np.histogram(generated, bins=len(x), density=True)\n", "diff = hist - pdf_values\n", "cdf_values = gauss.cdf(x)\n", "\n", "with plt.style.context(\"ggplot\"):\n", " fig, (ax1, ax2) = plt.subplots(2, sharex=True, figsize=(10, 10),\n", " gridspec_kw={'height_ratios': [2, 1]})\n", " ax1.set_title(\"A very important measurement\")\n", " ax1.grid(False)\n", " ax1.plot(x, pdf_values, label=\"PDF\")\n", " ax1.set_ylim(0)\n", " ax1.set_ylabel(\"Values\")\n", " ax1.hist(generated, bins=len(x), density=True, label=\"Histogram\")\n", " ax1.legend(loc=2, title=\"Legend\")\n", " ax1.text(3, 0.2, \"$N = 1000$\")\n", "\n", " ax3 = ax1.twinx()\n", " ax3.set_ylabel(\"CDF\")\n", " ax3.plot(x, cdf_values, \"g\", label=\"CDF\")\n", " ax3.set_ylim(0)\n", " \n", " ax2.step(bins[:-1], diff)\n", " ax2.set_xlim(-5, 5)\n", " ax2.set_ylabel(\"Residual\")\n", " ax2.set_xlabel(r\"$x_i$\")\n", "\n", " plt.savefig(\"plot_replication.png\")\n", " plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Geospatial data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Use `geopandas` to create an interesting visualization of data on a map.\n", "\n", "You can find a shapefile for the boroughs of London at the link https://data.london.gov.uk/dataset/statistical-gis-boundary-files-london. Download the file `statistical-gis-boundaries-london.zip`.\n", "\n", "For a lot of statistical data per borough, visit https://data.london.gov.uk/dataset/london-borough-profiles and download the `csv` file.\n", "\n", "Think about how to best join the two dataframes.\n", "\n", "Use the `plot` method of the `geopandas.DataFrame` to plot some statistics per borough. An example of what this can look like can be found below." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "![](geopandas_population.png)" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "ExecuteTime": { "end_time": "2020-06-26T14:39:40.165435Z", "start_time": "2020-06-26T14:39:39.957665Z" } }, "outputs": [], "source": [ "import geopandas" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "ExecuteTime": { "end_time": "2020-06-26T14:39:40.223738Z", "start_time": "2020-06-26T14:39:40.168275Z" } }, "outputs": [], "source": [ "df = geopandas.read_file(\"London_Borough_Excluding_MHW.shp\").set_index(\"GSS_CODE\")\n", "df = df.join(pd.read_csv(\"london-borough-profiles.csv\", header=0, encoding='iso-8859-1').set_index(\"Code\"))" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "ExecuteTime": { "end_time": "2020-06-26T14:39:40.230368Z", "start_time": "2020-06-26T14:39:40.225586Z" } }, "outputs": [ { "data": { "text/plain": [ "Index(['NAME', 'HECTARES', 'NONLD_AREA', 'ONS_INNER', 'SUB_2009', 'SUB_2006',\n", " 'geometry', 'Area_name', 'Inner/_Outer_London',\n", " 'GLA_Population_Estimate_2017', 'GLA_Household_Estimate_2017',\n", " 'Inland_Area_(Hectares)', 'Population_density_(per_hectare)_2017',\n", " 'Average_Age,_2017', 'Proportion_of_population_aged_0-15,_2015',\n", " 'Proportion_of_population_of_working-age,_2015',\n", " 'Proportion_of_population_aged_65_and_over,_2015',\n", " 'Net_internal_migration_(2015)', 'Net_international_migration_(2015)',\n", " 'Net_natural_change_(2015)',\n", " '%_of_resident_population_born_abroad_(2015)',\n", " 'Largest_migrant_population_by_country_of_birth_(2011)',\n", " '%_of_largest_migrant_population_(2011)',\n", " 'Second_largest_migrant_population_by_country_of_birth_(2011)',\n", " '%_of_second_largest_migrant_population_(2011)',\n", " 'Third_largest_migrant_population_by_country_of_birth_(2011)',\n", " '%_of_third_largest_migrant_population_(2011)',\n", " '%_of_population_from_BAME_groups_(2016)',\n", " '%_people_aged_3+_whose_main_language_is_not_English_(2011_Census)',\n", " 'Overseas_nationals_entering_the_UK_(NINo),_(2015/16)',\n", " 'New_migrant_(NINo)_rates,_(2015/16)',\n", " 'Largest_migrant_population_arrived_during_2015/16',\n", " 'Second_largest_migrant_population_arrived_during_2015/16',\n", " 'Third_largest_migrant_population_arrived_during_2015/16',\n", " 'Employment_rate_(%)_(2015)', 'Male_employment_rate_(2015)',\n", " 'Female_employment_rate_(2015)', 'Unemployment_rate_(2015)',\n", " 'Youth_Unemployment_(claimant)_rate_18-24_(Dec-15)',\n", " 'Proportion_of_16-18_year_olds_who_are_NEET_(%)_(2014)',\n", " 'Proportion_of_the_working-age_population_who_claim_out-of-work_benefits_(%)_(May-2016)',\n", " '%_working-age_with_a_disability_(2015)',\n", " 'Proportion_of_working_age_people_with_no_qualifications_(%)_2015',\n", " 'Proportion_of_working_age_with_degree_or_equivalent_and_above_(%)_2015',\n", " 'Gross_Annual_Pay,_(2016)', 'Gross_Annual_Pay_-_Male_(2016)',\n", " 'Gross_Annual_Pay_-_Female_(2016)',\n", " 'Modelled_Household_median_income_estimates_2012/13',\n", " '%_adults_that_volunteered_in_past_12_months_(2010/11_to_2012/13)',\n", " 'Number_of_jobs_by_workplace_(2014)',\n", " '%_of_employment_that_is_in_public_sector_(2014)', 'Jobs_Density,_2015',\n", " 'Number_of_active_businesses,_2015',\n", " 'Two-year_business_survival_rates_(started_in_2013)',\n", " 'Crime_rates_per_thousand_population_2014/15',\n", " 'Fires_per_thousand_population_(2014)',\n", " 'Ambulance_incidents_per_hundred_population_(2014)',\n", " 'Median_House_Price,_2015',\n", " 'Average_Band_D_Council_Tax_charge_(£),_2015/16',\n", " 'New_Homes_(net)_2015/16_(provisional)',\n", " 'Homes_Owned_outright,_(2014)_%',\n", " 'Being_bought_with_mortgage_or_loan,_(2014)_%',\n", " 'Rented_from_Local_Authority_or_Housing_Association,_(2014)_%',\n", " 'Rented_from_Private_landlord,_(2014)_%',\n", " '%_of_area_that_is_Greenspace,_2005', 'Total_carbon_emissions_(2014)',\n", " 'Household_Waste_Recycling_Rate,_2014/15',\n", " 'Number_of_cars,_(2011_Census)',\n", " 'Number_of_cars_per_household,_(2011_Census)',\n", " '%_of_adults_who_cycle_at_least_once_per_month,_2014/15',\n", " 'Average_Public_Transport_Accessibility_score,_2014',\n", " 'Achievement_of_5_or_more_A*-_C_grades_at_GCSE_or_equivalent_including_English_and_Maths,_2013/14',\n", " 'Rates_of_Children_Looked_After_(2016)',\n", " '%_of_pupils_whose_first_language_is_not_English_(2015)',\n", " '%_children_living_in_out-of-work_households_(2015)',\n", " 'Male_life_expectancy,_(2012-14)', 'Female_life_expectancy,_(2012-14)',\n", " 'Teenage_conception_rate_(2014)',\n", " 'Life_satisfaction_score_2011-14_(out_of_10)',\n", " 'Worthwhileness_score_2011-14_(out_of_10)',\n", " 'Happiness_score_2011-14_(out_of_10)',\n", " 'Anxiety_score_2011-14_(out_of_10)',\n", " 'Childhood_Obesity_Prevalance_(%)_2015/16',\n", " 'People_aged_17+_with_diabetes_(%)',\n", " 'Mortality_rate_from_causes_considered_preventable_2012/14',\n", " 'Political_control_in_council',\n", " 'Proportion_of_seats_won_by_Conservatives_in_2014_election',\n", " 'Proportion_of_seats_won_by_Labour_in_2014_election',\n", " 'Proportion_of_seats_won_by_Lib_Dems_in_2014_election',\n", " 'Turnout_at_2014_local_elections'],\n", " dtype='object')" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.columns" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "ExecuteTime": { "end_time": "2020-06-26T14:39:40.831597Z", "start_time": "2020-06-26T14:39:40.232867Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(1, figsize=(10, 6))\n", "df[\"GLA_Population_Estimate_2017\"] /= 1000\n", "df.plot(column=\"GLA_Population_Estimate_2017\", cmap=\"Blues\", linewidth=0.8, ax=ax, edgecolor='0.8')\n", "ax.axis('off')\n", "ax.set_title(\"London population estimate 2017\", fontdict={\"fontsize\": 25, \"fontweight\": 3})\n", "vmin, vmax = df[\"GLA_Population_Estimate_2017\"].min(), df[\"GLA_Population_Estimate_2017\"].max()\n", "sm = plt.cm.ScalarMappable(cmap='Blues', norm=plt.Normalize(vmin=vmin, vmax=vmax))\n", "sm._A = []\n", "cbar = fig.colorbar(sm, label=\"Thousand\")\n", "plt.savefig(\"geopandas_population.png\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# More tools" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Web scraping" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Use the `requests` library and `bs4.BeautifulSoup` to parse our homepage for the material of each lecture.\n", "Use the developer tools of your browser to figure out the names and attributes of elements.\n", "You can use CSS selectors using `soup.select`, or directly operate on the tags with `soup.find`/`soup.find_all`. \n", "\n", "Write a `download` function that automatically downloads the material to a specified directory. For this use `response.content`, instead of `response.text`, and `open(file_name, \"wb\")` in order to directly write the binary content to a file.\n", "Make sure to create the directory if it does not exist and that you deal with file names which would be illegal (for example file names containing `/`)." ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "ExecuteTime": { "end_time": "2020-06-26T14:39:41.216421Z", "start_time": "2020-06-26T14:39:40.833711Z" } }, "outputs": [], "source": [ "import requests\n", "from bs4 import BeautifulSoup\n", "from pathlib import Path\n", "import os\n", "\n", "def get_soup(session, url):\n", " \"\"\"Convenience function to use a session to get the soup of a webpage.\"\"\"\n", " response = session.get(url)\n", " response.raise_for_status()\n", " return BeautifulSoup(response.text, \"lxml\")\n", "\n", "def download(session, url, file_name, directory):\n", " response = sesstion.get(url) \n", " response.raise_for_status()\n", " directory = Path(directory)\n", " if not directory.exists():\n", " os.mkdir(directory)\n", " file_name = file_name.replace(\"/\", \"_\")\n", " with open(directory / file_name, \"wb\") as f:\n", " f.write(response.content)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "ExecuteTime": { "end_time": "2020-06-26T14:39:41.309900Z", "start_time": "2020-06-26T14:39:41.218767Z" } }, "outputs": [], "source": [ "session = requests.Session()\n", "base_url = \"https://www.physik.uzh.ch/~python/python\"\n", "soup = get_soup(session, f\"{base_url}/programme.php\")\n", "links = [a['href'] for a in soup.select(\"a.internal\")]" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "ExecuteTime": { "end_time": "2020-06-26T14:39:41.517925Z", "start_time": "2020-06-26T14:39:41.315529Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Best Practice / git\n", "https://www.physik.uzh.ch/~python/python/lecture_bp+git/best-practice.pdf\n", "https://www.physik.uzh.ch/~python/python/lecture_bp+git/git-tutorial.pdf\n", "https://www.physik.uzh.ch/~python/python/lecture_bp+git/exercise_single_local.txt\n", "https://www.physik.uzh.ch/~python/python/lecture_bp+git/exercise_multi_remote.txt\n", "https://www.physik.uzh.ch/~python/python/lecture_bp+git/single_local.txt\n", "https://www.physik.uzh.ch/~python/python/lecture_bp+git/multi_remote.txt\n", "\n", "Object-Oriented-Programming\n", "https://www.physik.uzh.ch/~python/python/lecture_oop/slides/oop_slides.pdf\n", "https://www.physik.uzh.ch/~python/python/lecture_oop/oopex.tar.gz\n", "https://www.physik.uzh.ch/~python/python/lecture_oop/oopsolution.tar.gz\n", "\n", "Test, Debug, Profile\n", "https://www.physik.uzh.ch/~python/python/lecture_tdp/test_debug_profile.pdf\n", "https://www.physik.uzh.ch/~python/python/lecture_tdp/demo_code.zip\n", "https://www.physik.uzh.ch/~python/python/lecture_tdp/tdp_exercise.pdf\n", "https://www.physik.uzh.ch/~python/python/lecture_tdp/maxima.py\n", "https://www.physik.uzh.ch/~python/python/lecture_tdp/tdp_solutions.zip\n", "https://www.physik.uzh.ch/~python/python/lecture_tdp/software_carpentry_cheatsheets_v1_6.pdf\n", "https://www.physik.uzh.ch/~python/python/lecture_tdp/additional.pdf\n", "https://www.physik.uzh.ch/~python/python/lecture_tdp/carpentry_exercise.zip\n", "https://www.physik.uzh.ch/~python/python/lecture_tdp/Unittest_in_Jupyter.html\n", "\n", "Pandas Tutorial\n", "https://www.physik.uzh.ch/~python/python/lecture_pandas/Refugees.ipynb\n", "https://www.physik.uzh.ch/~python/python/lecture_pandas/Refugees.html\n", "https://www.physik.uzh.ch/~python/python/lecture_pandas/Refugees.pdf\n", "https://www.physik.uzh.ch/~python/python/lecture_pandas/data.zip\n", "https://www.physik.uzh.ch/~python/python/lecture_pandas/Lecture_ipython.html\n", "https://www.physik.uzh.ch/~python/python/lecture_pandas/material_ipython_lec.zip\n", "\n", "NumPy, Pandas and beyond\n", "https://www.physik.uzh.ch/~python/python/lecture_data/data_structures_lecture_material.zip\n", "https://www.physik.uzh.ch/~python/python/lecture_data/data_structures_exercise_material.zip\n", "https://www.physik.uzh.ch/~python/python/lecture_data/data_structures_exercise_solution_material.zip\n", "\n", "Scientific Analytics\n", "https://www.physik.uzh.ch/~python/python/lecture_analysis/che_analytics.pdf\n", "https://www.physik.uzh.ch/~python/python/lecture_analysis/material_analysis_lec.zip\n", "https://www.physik.uzh.ch/~python/python/lecture_analysis/Analytics_ex.pdf\n", "https://www.physik.uzh.ch/~python/python/lecture_analysis/material_analysis_ex.zip\n", "\n", "Python meets C/C++\n", "https://www.physik.uzh.ch/~python/python/lecture_c++/che_pythoncpp.pdf\n", "https://www.physik.uzh.ch/~python/python/lecture_c++/material_Python_C_lec.zip\n", "https://www.physik.uzh.ch/~python/python/lecture_c++/Python_C_ex.pdf\n", "https://www.physik.uzh.ch/~python/python/lecture_c++/material_Python_C_ex.zip\n", "\n", "Hardware-assisted speed-up techniques\n", "https://www.physik.uzh.ch/~python/python/lecture_hwaccel/ex/Python_hwaccel_ex.pdf\n", "https://www.physik.uzh.ch/~python/python/lecture_hwaccel/ex/hwaccelex.tar.gz\n", "\n", "Visualisation and More\n", "https://www.physik.uzh.ch/~python/python/lecture_visual/visualization.pdf\n", "https://www.physik.uzh.ch/~python/python/lecture_visual/Visualization.ipynb\n", "https://www.physik.uzh.ch/~python/python/lecture_visual/exercise.pdf\n", "https://www.physik.uzh.ch/~python/python/lecture_visual/london.zip\n", "https://www.physik.uzh.ch/~python/python/lecture_visual/Exercises_solution.ipynb\n", "\n" ] } ], "source": [ "for link in links:\n", " soup = get_soup(session, f\"{base_url}/{link}\")\n", " print(soup.title.text.split(\" - \")[-1])\n", " for file_name in [a['href'] for a in soup.select(\"a.download\")]:\n", " url = f\"{base_url}/{link}/{file_name}\"\n", " print(url)\n", " # uncomment this to actually download the files\n", " # download(session, url, file_name, \".\")\n", " print()" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.9" }, "latex_envs": { "LaTeX_envs_menu_present": true, "autoclose": false, "autocomplete": true, "bibliofile": "biblio.bib", "cite_by": "apalike", "current_citInitial": 1, "eqLabelWithNumbers": true, "eqNumInitial": 1, "hotkeys": { "equation": "Ctrl-E", "itemize": "Ctrl-I" }, "labels_anchors": false, "latex_user_defs": false, "report_style_numbering": false, "user_envs_cfg": false }, "toc": { "base_numbering": 1, "nav_menu": {}, "number_sections": true, "sideBar": true, "skip_h1_title": false, "title_cell": "Table of Contents", "title_sidebar": "Contents", "toc_cell": false, "toc_position": { "height": "calc(100% - 180px)", "left": "10px", "top": "150px", "width": "384px" }, "toc_section_display": true, "toc_window_display": true } }, "nbformat": 4, "nbformat_minor": 2 }