{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# *Statistics coded*: \"Social media - statistics on the use by enterprises\"\n",
    "\n",
    "Prepared by [**beatrizq**](beatriz.querido@gmail.com) ([LinkedIn](https://www.linkedin.com/in/beatrizque/)).\n",
    "\n",
    "This notebook aims at reproducing the figures of the original *Statistics Explained* article on [**social media - statistics on the use by enterprises**](https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Social_media_-_statistics_on_the_use_by_enterprises)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Configuration\n",
    "\n",
    "- Installing the [_Eurostat_ API](https://github.com/opus-42/eurostat-api-client)\n",
    "- Importing the necessary libraries for data representation, extraction and visualization, as well as specific dependencies of the API\n",
    "- Adjusting the settings for the API"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#data representation\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "#data extraction\n",
    "#pip install eurostatapiclient --no-dependencies\n",
    "#conda install eurostatapiclient --no-deps\n",
    "import requests\n",
    "import certifi\n",
    "import chardet\n",
    "import idna\n",
    "import pytz\n",
    "import six\n",
    "import urllib3\n",
    "import dateutil\n",
    "from eurostatapiclient import EurostatAPIClient\n",
    "\n",
    "#data visualization\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.ticker as ticker\n",
    "import matplotlib.patches as mpatches\n",
    "from matplotlib.lines import Line2D\n",
    "import matplotlib.patches as mpatches\n",
    "import seaborn as sns\n",
    "\n",
    "#settings for EurostatAPIClient\n",
    "VERSION = 'v2.1'\n",
    "FORMAT = 'json'\n",
    "LANGUAGE = 'en'\n",
    "client = EurostatAPIClient(VERSION, FORMAT, LANGUAGE)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data extraction\n",
    "\n",
    "In order to load the relevant data, these steps were followed:\n",
    "- use the Eurostat query builder for `JSON`-stat format Web Services to filter the relevant datasets, using the respective dataset code and according to the codes explained below;\n",
    "- use the generated query code as parameter for the client.get_dataset function (included in the `EurostatAPIClient` library)\n",
    "\n",
    "Relevant datasets considered were:\n",
    "- `\"isoc_cismt\"`: Social media use by type, internet advertising\n",
    "- `\"isoc_cismp\"`: Social media use by purpose"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "### FILTER CODES ###\n",
    "\n",
    "#UNIT:\n",
    "#% of enterprises: PC_ENT\n",
    "#% of enterprises using social media: PC_ENT_SM\n",
    "\n",
    "#SIZE:\n",
    "#large: L_C10_S951_XK\n",
    "#medium: M_C10_S951_XK\n",
    "#small: S_C10_S951_XK\n",
    "\n",
    "#PURPOSE:\n",
    "#develop=E_SM_PADVERT\n",
    "#obtain=E_SM_PCUQOR\n",
    "#recruit=E_SM_PRCR\n",
    "#involve=E_SM_PCUDEV\n",
    "#exchange = E_SM_PEXCHVOC\n",
    "#collaborate = E_SM_PBPCOLL\n",
    "\n",
    "#TYPE OF SOCIAL MEDIA:\n",
    "#only one type of social media = E_SM1_1\n",
    "#any social media = E_SM1_ANY\n",
    "#two or more types = E_SM1_GE2\n",
    "#enterprise's blog or microblogs = E_SM1_BLOG\n",
    "#multimedia content sharing websites = E_SM1_CNTSHR\n",
    "#social networks = E_SM1_SNET\n",
    "#wiki based knowledge sharing tools = E_SM1_WIKI\n",
    "\n",
    "#ACTIVITY:\n",
    "#transportation and storage = 10_H49_53\n",
    "#construction = 10_F41_43\n",
    "#electricity = 10_D35_E39\n",
    "#administrative = 10_N77_82\n",
    "#professional = 10_M69_74\n",
    "#manufacturing = 10_C10_33\n",
    "#information = 10_J58_63\n",
    "#real estate = 10_L68\n",
    "#wholesale = 10_G45_47\n",
    "#retail trade = 10_G47\n",
    "#accommodation = 10_I55"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Use of social media by enterprises\n",
    "\n",
    "Table 1: Enterprises using social media, 2019, (% of enterprises) - Source: _Eurostat_ ([isoc_cismt](https://www.coursera.org/specializations/deep-learning#courses))\n",
    "\n",
    "### Table 1\n",
    "\n",
    "#### Step 1: Understanding the table\n",
    "\n",
    "- it shows the percentage of enterprises using each type of social media in each country, in 2019;\n",
    "- countries are represented in the rows; social media types correspond to the columns\n",
    "\n",
    "#### Step 2: Data extraction and preparation\n",
    "\n",
    "- dataset code used: `\"isoc_cismt\"`;\n",
    "- all relevant data was imported into a single dataframe and then:\n",
    "    - restructured: using the `set_index` and `unstack` commands to convert the social media entries        in the original indic_is column into new columns;\n",
    "    - reordered: using the `loc` command to form a new dataframe according to the original row and column orders;\n",
    "    - renamed: using the `rename* command to replace codes with the proper strings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "#TABLE 1: data extraction\n",
    "#source: Eurostat API (isoc_cismt)\n",
    "\n",
    "#get data\n",
    "table1_source = 'isoc_cismt?precision=1&geo=AT&geo=BA&geo=BE&geo=BG&geo=CY&geo=CZ&geo=DE&geo=DK&geo=EE&geo=EL&geo=ES&geo=EU28&geo=FI&geo=FR&geo=HR&geo=HU&geo=IE&geo=IS&geo=IT&geo=LT&geo=LU&geo=LV&geo=ME&geo=MT&geo=NL&geo=NO&geo=PL&geo=PT&geo=RO&geo=RS&geo=SE&geo=SI&geo=SK&geo=TR&geo=UK&unit=PC_ENT&indic_is=E_SM1_1&indic_is=E_SM1_ANY&indic_is=E_SM1_BLOG&indic_is=E_SM1_CNTSHR&indic_is=E_SM1_GE2&indic_is=E_SM1_SNET&indic_is=E_SM1_WIKI&sizen_r2=10_C10_S951_XK&unitLabel=label&time=2019'\n",
    "\n",
    "df_table1 = client.get_dataset(table1_source).to_dataframe()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "#TABLE 1: data preparation\n",
    "\n",
    "df_table1_restructured = df_table1.loc[:,['values','indic_is','geo']].set_index(['geo', 'indic_is'])['values'].unstack()\n",
    "\n",
    "order_col = ['E_SM1_SNET', 'E_SM1_BLOG', 'E_SM1_CNTSHR', 'E_SM1_WIKI', 'E_SM1_1', 'E_SM1_GE2', 'E_SM1_ANY']\n",
    "order_row = ['EU28','BE','BG','CZ','DK','DE','EE','IE','EL','ES','FR','HR','IT','CY','LV','LT','LU','HU','MT','NL','AT','PL','PT','RO','SI','SK','FI','SE','UK','IS','NO','ME','RS','TR','BA']\n",
    "\n",
    "df_table1_reordered = df_table1_restructured.loc[order_row, order_col]\n",
    "\n",
    "countries_names = {'AT':'Austria', 'BE':'Belgium', 'BG':'Bulgaria', 'CY': 'Cyprus', 'CZ': 'Czechia', 'DE': 'Germany', 'DK':'Denmark', 'EE':'Estonia', 'EL': 'Greece', 'ES':'Spain', 'FI':'Finland', 'FR':'France', 'HR':'Croatia', 'HU':'Hungary', 'IE':'Ireland', 'IT':'Italy', 'LT':'Lithuania', 'LU':'Luxembourg', 'LV':'Latvia', 'MT':'Malta', 'NL':'Netherlands', 'PL':'Poland', 'PT':'Portugal', 'RO':'Romania', 'SE':'Sweden', 'SI':'Slovenia','SK':'Slovakia', 'UK':'United Kingdom', 'EU28': 'EU-28','TR':'Turkey','CH':'Switzerland', 'IS':'Iceland', 'MK':'North Macedonia','ME':'Montenegro',\n",
    "'NO':'Norway', 'RS': 'Serbia', 'BA': 'Bosnia and Herzegovina'}\n",
    "\n",
    "media_types = {'E_SM1_SNET':'Social networks', 'E_SM1_CNTSHR':'Multimedia content-sharing websites', 'E_SM1_BLOG':'Enterprise blog or microblogs', 'E_SM1_WIKI':'Wiki-based knowledge- sharing tools', 'E_SM1_1': 'Use only one type of social media (*)', 'E_SM1_GE2':'Use two or more types of social media (*)', 'E_SM1_ANY': 'Use at least one type of social media (*)'}\n",
    "\n",
    "df_table1_renamed = df_table1_reordered.rename(countries_names, axis='index')\n",
    "df_table1_renamed = df_table1_renamed.rename(media_types, axis='columns')\n",
    "#df_table1_renamed.index.name = None\n",
    "#print(df_table1_renamed)\n",
    "df_table1_renamed.style"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Types of social media used over time (2013-2019)\n",
    "\n",
    "### Figure 1\n",
    "\n",
    "#### Step 1: Understanding the graph\n",
    "\n",
    "- the graph corresponds to a line plot\n",
    "- each line represents a different type of social media and shows the percentage of enterprises using that specific type over time\n",
    "\n",
    "#### Step 2: Data extraction and preparation\n",
    "\n",
    "- dataset code used: `\"isoc_cismt\"`;\n",
    "- as any indicators for the year 2013 were distinguished from the rest, we had to import data from that year and data from the other years separately and combine the two dataframes together afterwards; \n",
    "- we then created a dataframe for each type of social media containing the percentage values per year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "#FIGURE 1: data\n",
    "#source: Eurostat API (isoc_cismt)\n",
    "\n",
    "#get data\n",
    "figure1a_source = 'isoc_cismt?precision=1&geo=EU28&unit=PC_ENT&indic_is=E_SM_BLOG&indic_is=E_SM_CNTSHR&indic_is=E_SM_SNET&indic_is=E_SM_WIKI&sizen_r2=10_C10_S951_XK&unitLabel=label&time=2013&time=2015&time=2017&time=2019'\n",
    "dataframe_figure1a = client.get_dataset(figure1a_source).to_dataframe()\n",
    "\n",
    "figure1b_source = 'isoc_cismt?groupedIndicators=1&precision=1&geo=EU28&unit=PC_ENT&indic_is=E_SM1_BLOG&indic_is=E_SM1_CNTSHR&indic_is=E_SM1_SNET&indic_is=E_SM1_WIKI&sizen_r2=10_C10_S951_XK&unitLabel=label&time=2013&time=2015&time=2017&time=2019'\n",
    "dataframe_figure1b = client.get_dataset(figure1b_source).to_dataframe()\n",
    "\n",
    "dataframe_figure1 = dataframe_figure1a.copy().fillna(dataframe_figure1b)\n",
    "\n",
    "dataframe_figure1_blog = dataframe_figure1.loc[dataframe_figure1['indic_is'] == 'E_SM_BLOG'].groupby(by = 'time')['values'].sum()\n",
    "dataframe_figure1_cntshr = dataframe_figure1.loc[dataframe_figure1['indic_is'] == 'E_SM_CNTSHR'].groupby(by = 'time')['values'].sum()\n",
    "dataframe_figure1_snet = dataframe_figure1.loc[dataframe_figure1['indic_is'] == 'E_SM_SNET'].groupby(by = 'time')['values'].sum()\n",
    "dataframe_figure1_wiki = dataframe_figure1.loc[dataframe_figure1['indic_is'] == 'E_SM_WIKI'].groupby(by = 'time')['values'].sum()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Step 3: Plotting\n",
    "\n",
    "- all plotting functions belong to the `matplotlib` library; \n",
    "- first off, we created the figure and axis and established the image size;\n",
    "- then, we configured layout elements such as the sheet style, grid, spines and size of the labels;\n",
    "- the axis were also adjusted, regarding the ticks and limit;\n",
    "- using the `plt.plot` command, we plotted the lines while setting different colors and specifying the `linestyle`;\n",
    "- legends representing each social media type were first created separately and then displayed in a specific way: next to each other or on top of each other; \n",
    "- finally, the title was created, minding the original line breaks \n",
    "\n",
    "**NB. These steps apply to all figures and will not be repeated throughout this notebook's explanation sections**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(-0.03, 1.05, 'Enterprises using social media, by type of social media, EU-28, \\n2013, 2015, 2017 and 2019 \\n(% of enterprises)')"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
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   "source": [
    "#FIGURE 1: graph\n",
    "\n",
    "#size of graph\n",
    "fig, ax = plt.subplots(figsize=(10, 4))\n",
    "\n",
    "#grid\n",
    "plt.style.use('default') #aesthetic of sheet\n",
    "ax.grid(True, which = 'major', axis = 'y' , color ='grey', linestyle = '-', alpha = 0.2) #grey lines\n",
    "sns.despine(top=True, right=True, left=True, bottom=False) #remove spines\n",
    "ax.tick_params(axis = 'both',which = 'major' , labelsize = 8) #size of labels in axis\n",
    "\n",
    "#scale of graph\n",
    "plt.ylim(0,61)\n",
    "plt.yticks(np.arange(0, 61, step=10))\n",
    "\n",
    "#plot the data\n",
    "plt.plot(dataframe_figure1_blog, color='orange', marker ='^')\n",
    "plt.plot(dataframe_figure1_cntshr, color='royalblue', marker ='D', linestyle = 'dashed')\n",
    "plt.plot(dataframe_figure1_snet, color='darkorange', marker ='s')\n",
    "plt.plot(dataframe_figure1_wiki, color='seagreen', marker ='o')\n",
    "\n",
    "#legend\n",
    "leg_snet = Line2D([0],[0], lw=4, color='darkorange', label='Social networks', marker='s')\n",
    "leg_cntshr = Line2D([0],[0], lw=4, color='royalblue', label='Multimedia content- \\n sharing websites', marker='D')\n",
    "leg_blog = Line2D([0],[0], lw=4, color='orange', label='Enterprise blog \\n or microblogs', marker='^')\n",
    "leg_wiki = Line2D([0],[0], lw=4, color='seagreen', label='Wiki-based knowledge- \\n sharing tools', marker='o')\n",
    "\n",
    "leg = ax.legend(handles=[leg_snet,leg_cntshr,leg_blog,leg_wiki], frameon=False, loc=(0.15, -.26), ncol=4, prop={'weight':'bold','size':'7'}, labelspacing=0.5, handlelength=0.5)\n",
    "\n",
    "#title\n",
    "ax.set_title('Enterprises using social media, by type of social media, EU-28, \\n2013, 2015, 2017 and 2019 \\n(% of enterprises)', fontsize=10, fontweight='bold', horizontalalignment = 'left', x = -0.03, y =1.05)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Figure 1: Enterprises using social media, by type of social media, EU-28, 2013, 2015, 2017 and 2019 (% of enterprises)  - Source: Eurostat ([isoc_cismt](https://www.coursera.org/specializations/deep-learning#courses))"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Figure 2\n",
    "\n",
    "#### Step 1: Understanding the graph\n",
    "\n",
    "- the graph corresponds to a stacked bar plot\n",
    "- each bar represents the percentage of enterprises using social networks specifically in 2013 (at the bottom) and in 2019 (on top), in the EU-28 and per country\n",
    "\n",
    "#### Step 2: Data extraction and preparation\n",
    "\n",
    "- dataset code used: `\"isoc_cismt\"`;\n",
    "- once again, data from 2013 and data from 2019 were imported separately into two different dataframes\n",
    "- then, for each of them, we distinguished data for countries that belong to the EU-28 from data for countries that do not and from data for the EU-28 alone;\n",
    "- we ordered the EU-28 countries by sorting their 2019 values by descending order and then combined all countries together as: Eu-28 first, EU-28 countries second, not-EU-28 countries last;\n",
    "- the order for 2013 values was established according to the 2019 order and by using the set_index and reindex commands;\n",
    "- country codes were replaced with the proper names;\n",
    "- finally, in order to space out bars from different original dataframes we included \"filler\" instances in the final dataframes;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "#FIGURE 2: data\n",
    "#source: Eurostat API (isoc_cismt)\n",
    "\n",
    "countries_names = {'AT':'Austria', 'BE':'Belgium', 'BG':'Bulgaria', 'CY': 'Cyprus', 'CZ': 'Czechia', 'DE': 'Germany', 'DK':'Denmark', 'EE':'Estonia', 'EL': 'Greece', 'ES':'Spain', 'FI':'Finland', 'FR':'France', 'HR':'Croatia', 'HU':'Hungary', 'IE':'Ireland', 'IT':'Italy', 'LT':'Lithuania', 'LU':'Luxembourg', 'LV':'Latvia', 'MT':'Malta', 'NL':'Netherlands', 'PL':'Poland', 'PT':'Portugal', 'RO':'Romania', 'SE':'Sweden', 'SI':'Slovenia','SK':'Slovakia', 'UK':'United Kingdom', 'EU28': 'EU-28', 'TR':'Turkey','CH':'Switzerland', 'IS':'Iceland', 'MK':'North Macedonia','ME':'Montenegro',\n",
    "'NO':'Norway', 'RS': 'Serbia'}\n",
    "\n",
    "#get data\n",
    "figure2_2013_source = 'isoc_cismt?precision=1&geo=AT&geo=BE&geo=BG&geo=CY&geo=CZ&geo=DE&geo=DK&geo=EE&geo=EL&geo=ES&geo=EU28&geo=FI&geo=FR&geo=HR&geo=HU&geo=IE&geo=IS&geo=IT&geo=LT&geo=LU&geo=LV&geo=MT&geo=NL&geo=NO&geo=PL&geo=PT&geo=RO&geo=SE&geo=SI&geo=SK&geo=UK&unit=PC_ENT&indic_is=E_SM_SNET&sizen_r2=10_C10_S951_XK&unitLabel=label&time=2013'\n",
    "dataframe_figure2_2013 = client.get_dataset(figure2_2013_source).to_dataframe()\n",
    "\n",
    "figure2_2019_source = 'isoc_cismt?precision=1&geo=AT&geo=BE&geo=BG&geo=CY&geo=CZ&geo=DE&geo=DK&geo=EE&geo=EL&geo=ES&geo=EU28&geo=FI&geo=FR&geo=HR&geo=HU&geo=IE&geo=IS&geo=IT&geo=LT&geo=LU&geo=LV&geo=MT&geo=NL&geo=NO&geo=PL&geo=PT&geo=RO&geo=SE&geo=SI&geo=SK&geo=UK&unit=PC_ENT&indic_is=E_SM1_SNET&sizen_r2=10_C10_S951_XK&unitLabel=label&time=2019'\n",
    "dataframe_figure2_2019 = client.get_dataset(figure2_2019_source).to_dataframe()\n",
    "\n",
    "#organize 2019 layer\n",
    "dataframe_figure2_2019_eu28 = dataframe_figure2_2019[dataframe_figure2_2019['geo'] == 'EU28']\n",
    "\n",
    "dataframe_figure2_2019_onlyEU = dataframe_figure2_2019[(dataframe_figure2_2019.geo != 'NO') & (dataframe_figure2_2019.geo != 'IS') & (dataframe_figure2_2019.geo != 'EU28')].sort_values(by = ['values'],ascending = False)\n",
    "\n",
    "dataframe_figure2_2019_notEU = dataframe_figure2_2019[(dataframe_figure2_2019['geo'] == 'NO') | (dataframe_figure2_2019['geo'] == 'IS')].sort_values(by = ['values'],ascending = False)\n",
    "\n",
    "dataframe_figure2_2019_sorted = pd.concat([dataframe_figure2_2019_eu28, dataframe_figure2_2019_onlyEU, dataframe_figure2_2019_notEU], ignore_index=False).reset_index()\n",
    "\n",
    "#organize 2013 layer\n",
    "dataframe_figure2_2013_sorted = dataframe_figure2_2013.set_index('geo')\n",
    "dataframe_figure2_2013_sorted = dataframe_figure2_2013_sorted.reindex(index=dataframe_figure2_2019_sorted['geo'])\n",
    "dataframe_figure2_2013_sorted = dataframe_figure2_2013_sorted.reset_index()\n",
    "\n",
    "#replace names\n",
    "dataframe_figure2_2013_sorted = dataframe_figure2_2013_sorted.replace({'geo':countries_names})\n",
    "dataframe_figure2_2019_sorted = dataframe_figure2_2019_sorted.replace({'geo':countries_names})\n",
    "\n",
    "figure2_bars_2019 = dataframe_figure2_2019_sorted['values'].tolist()\n",
    "figure2_bars_2013 = dataframe_figure2_2013_sorted['values'].tolist()\n",
    "figure2_bars_2019_dif = [a - b for a,b in zip(figure2_bars_2019,figure2_bars_2013)]\n",
    "\n",
    "figure2_countries = dataframe_figure2_2019_sorted['geo'].tolist()\n",
    "\n",
    "#add \"empty\" bars\n",
    "figure2_2019_spaced = figure2_bars_2019_dif.copy()\n",
    "figure2_2019_spaced.insert(1,0)\n",
    "figure2_2019_spaced.insert(30,0)\n",
    "\n",
    "figure2_2013_spaced = figure2_bars_2013.copy()\n",
    "figure2_2013_spaced.insert(1,0)\n",
    "figure2_2013_spaced.insert(30,0)\n",
    "\n",
    "figure2_countries_spaced = figure2_countries.copy()\n",
    "figure2_countries_spaced.insert(1,'space')\n",
    "figure2_countries_spaced.insert(30,'space')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Step 3: Plotting\n",
    "\n",
    "- the way we established the position of each bar was by adjusting the `xticks` according to the length of the array containing the countries' names: using `range(len())` command\n",
    "- for stacking the 2013 bars on top, we specified the \"bottom\" parameter as the 2019 bars instead of the default x-axis;\n",
    "- in order to display the 2013 values inside the bars, we used a for loop that extracted the bar's height, which in this case corresponded to the percentage value, and placed it according to the bar's position on the x-axis and to a fraction of the height's value\n",
    "- in the case of the 2019 values, the bar's height did not correspond to the percentage value and so the height values of both 2013 and 2019 bars for the same xticks had to be added together\n",
    "- finally, the percentage values for the \"filler\" instances were not displayed, by using an if condition, as well as their axis labels (by coloring them in white)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(-0.045, 1.05, 'Enterprises using social networks, 2013 and 2019 \\n(% of enterprises)')"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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       "      </g>\r\n",
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       "      <!-- Croatia -->\r\n",
       "      <g transform=\"translate(375.56921 300.676125)rotate(-90)scale(0.08 -0.08)\">\r\n",
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       "     <g id=\"line2d_22\">\r\n",
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       "      <g transform=\"translate(422.107992 303.223625)rotate(-90)scale(0.08 -0.08)\">\r\n",
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       "     </g>\r\n",
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       "    <g id=\"xtick_25\">\r\n",
       "     <g id=\"line2d_25\">\r\n",
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       "     </g>\r\n",
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       "    <g id=\"xtick_26\">\r\n",
       "     <g id=\"line2d_26\">\r\n",
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       "    </g>\r\n",
       "    <g id=\"xtick_27\">\r\n",
       "     <g id=\"line2d_27\">\r\n",
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       "      <g transform=\"translate(468.646774 306.083625)rotate(-90)scale(0.08 -0.08)\">\r\n",
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      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
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     "metadata": {},
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   ],
   "source": [
    "#FIGURE 2: graph\n",
    "\n",
    "r = range(len(figure2_countries_spaced))\n",
    "\n",
    "figure2_years = ['2013','2019']\n",
    "\n",
    "colors = ['tomato', 'royalblue']\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(10, 4))\n",
    "ax.grid(True, which = 'major', axis = 'y', color ='grey', linestyle = '-', alpha = 0.2) #grey lines\n",
    "sns.despine(top=True, right=True, left=True, bottom=False) #remove spines\n",
    "ax.set_axisbelow(True) #set the grid below the bars\n",
    "plt.xticks(r, figure2_countries_spaced, rotation= 90) #x labels\n",
    "ax.set_ylim(0, 101)\n",
    "ax.tick_params(axis = 'both', which = 'major', labelsize = 8) #size of labels in axis\n",
    "plt.yticks(np.arange(0, 101, step=10))\n",
    "\n",
    "ax.get_xticklabels()[1].set_color(\"w\")\n",
    "ax.get_xticklabels()[30].set_color(\"w\")\n",
    "\n",
    "barWidth = 0.7\n",
    "bars_2013 = plt.bar(r, figure2_2013_spaced, color=colors[0], width=barWidth, label=figure2_years[0])\n",
    "\n",
    "bars_2019 = plt.bar(r, figure2_2019_spaced, bottom=figure2_2013_spaced, color=colors[1], width=barWidth, label=figure2_years[1])\n",
    "\n",
    "i = 0\n",
    "for bar_2013, bar_2019 in zip(bars_2013,bars_2019):\n",
    "    h_2013 = bar_2013.get_height()\n",
    "    h_2019 = bar_2019.get_height()\n",
    "    x_2013 = bar_2013.get_x()\n",
    "    x_2019 = bar_2019.get_x()\n",
    "    x = x_2013 + x_2019\n",
    "    h = h_2013 + h_2019\n",
    "    #c = np.where(bars_2013[bar_2013]=='space','white','black')\n",
    "    #c = np.where(bars_2013.index()==1,'white','black')\n",
    "    if (i != 1) and (i != 30):\n",
    "        plt.text(x_2019 + barWidth/6.5, h + 2, h, fontsize='x-small')\n",
    "        plt.text(x_2013 + barWidth/6.5, h_2013 - 5, h_2013, fontsize='x-small')\n",
    "    i = i+1\n",
    "\n",
    "#legend\n",
    "leg_2019 = Line2D([0],[0], lw=4, color='tomato', label='2019', marker='s')\n",
    "leg_2013 = Line2D([0],[0], lw=4, color='royalblue', label='2013', marker='s')\n",
    "\n",
    "leg = ax.legend(handles=[leg_2019,leg_2013], frameon=False, loc=(0.4, -.4), ncol=2, prop={'weight':'bold','size':'7'}, labelspacing=0.5, handlelength=0.5)\n",
    "\n",
    "ax.set_title('Enterprises using social networks, 2013 and 2019 \\n(% of enterprises)', fontsize=10, fontweight='bold', horizontalalignment = 'left', x = -0.045, y =1.05)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Types of social media used by enterprise size and economic activity\n",
    "\n",
    "### Figure 3\n",
    "\n",
    "#### Step 1: Understanding the graph\n",
    "\n",
    "- the graph corresponds to a grouped-bar plot\n",
    "- each group of bars corresponds to a different type of social media and each bar within a group represents a different enterprise size class\n",
    "- the values displayed show the percentage of enterprises using social media\n",
    "\n",
    "#### Step 2: Data extraction and preparation\n",
    "\n",
    "- dataset code used: `\"isoc_cismt\"`;\n",
    "- the dataframes were created according to the different size classes and display the percentage values in a specific order: social network first, multi-media sharing websites second, blog or microblogs third and wiki-based tools last;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "#FIGURE 3: data\n",
    "#source: Eurostat API (isoc_cismt)\n",
    "\n",
    "#get data\n",
    "figure3_source = 'isoc_cismt?precision=1&geo=EU28&unit=PC_ENT&indic_is=E_SM1_BLOG&indic_is=E_SM1_CNTSHR&indic_is=E_SM1_SNET&indic_is=E_SM1_WIKI&sizen_r2=L_C10_S951_XK&sizen_r2=M_C10_S951_XK&sizen_r2=S_C10_S951_XK&unitLabel=label&time=2019'\n",
    "\n",
    "dataframe_figure3 = client.get_dataset(figure3_source).to_dataframe().set_index('indic_is')\n",
    "\n",
    "media_order = ['E_SM1_SNET','E_SM1_CNTSHR','E_SM1_BLOG','E_SM1_WIKI']\n",
    "\n",
    "figure3_bars_large = dataframe_figure3[(dataframe_figure3['sizen_r2'] == 'L_C10_S951_XK')].reindex(media_order)['values'].tolist()\n",
    "\n",
    "figure3_bars_medium = dataframe_figure3[(dataframe_figure3['sizen_r2'] == 'M_C10_S951_XK')].reindex(media_order)['values'].tolist()\n",
    "\n",
    "figure3_bars_small = dataframe_figure3[(dataframe_figure3['sizen_r2'] == 'S_C10_S951_XK')].reindex(media_order)['values'].tolist()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Step 3: Plotting\n",
    "\n",
    "- once again, the way we established the position of each bar was by adjusting the xticks according to the length of the array containing the social media types: using `range(len())` command\n",
    "- for ordering the bars within each group, we represented the medium class values in the middle of the xtick and the bars for the other classes on the left/right side, either by substracting or by adding one bar's width value to the original xtick;\n",
    "- the values on top of the bars were displayed by using their height and x-position values as coordinates, with a little spacing adjustment; "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      ],
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#FIGURE 3: graph\n",
    "\n",
    "media_types = ['Social networks','Multimedia content- \\n sharing websites','Enterprise blog \\n or microblogs','Wiki-based knowledge- \\n sharing tools']\n",
    "\n",
    "sizes = ['large','medium','small']\n",
    "\n",
    "colors = ['tomato', 'royalblue', 'cornflowerblue']\n",
    "\n",
    "r = np.arange(len(media_types))\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(10, 4))\n",
    "ax.grid(True, which = 'major', axis = 'y', color ='grey', linestyle = '-', alpha = 0.2) #grey lines\n",
    "sns.despine(top=True, right=True, left=True, bottom=False) #remove spines\n",
    "ax.set_axisbelow(True) #set the grid below the bars\n",
    "plt.xticks(r, media_types, rotation= 0) #x labels\n",
    "ax.set_ylim(0, 81)\n",
    "ax.tick_params(axis = 'both', which = 'major', labelsize = 8) #size of labels in axis\n",
    "plt.yticks(np.arange(0, 81, step=10))\n",
    "barWidth = 0.2 #width of bars\n",
    "\n",
    "bars_large = plt.bar(r - barWidth, figure3_bars_large, color=colors[0], width=barWidth, label=sizes[0])\n",
    "\n",
    "bars_medium = plt.bar(r, figure3_bars_medium, color=colors[1], width=barWidth, label=sizes[1])\n",
    "\n",
    "bars_small = plt.bar(r + barWidth, figure3_bars_small, color=colors[2], width=barWidth, label=sizes[2])\n",
    "\n",
    "for bars_large, bars_medium, bars_small in zip(bars_large,bars_medium,bars_small):\n",
    "    h_large = bars_large.get_height()\n",
    "    h_medium = bars_medium.get_height()\n",
    "    h_small = bars_small.get_height()\n",
    "    x_large = bars_large.get_x()\n",
    "    x_medium = bars_medium.get_x()\n",
    "    x_small = bars_small.get_x()\n",
    "    plt.text(x_large + barWidth/3, h_large +2, h_large, fontsize='x-small')\n",
    "    plt.text(x_medium + barWidth/3, h_medium +2, h_medium, fontsize='x-small')\n",
    "    plt.text(x_small + barWidth/3, h_small +2, h_small, fontsize='x-small')\n",
    "\n",
    "#title\n",
    "ax.set_title('Enterprises using social media, by type and size class, EU-28, 2019 \\n(% of enterprises)', fontsize=10, fontweight='bold', horizontalalignment = 'left', x = 0.0, y =1.05)\n",
    "\n",
    "#legend\n",
    "leg_large = Line2D([0],[0], lw=4, color='tomato', label='large', marker='s')\n",
    "leg_medium = Line2D([0],[0], lw=4, color='royalblue', label='medium', marker='s')\n",
    "leg_small = Line2D([0],[0], lw=4, color='cornflowerblue', label='small', marker='s')\n",
    "\n",
    "leg = ax.legend(handles=[leg_large,leg_medium,leg_small], frameon=False, loc=(0.38, -0.26), ncol=3, prop={'weight':'bold','size':'7'}, labelspacing=0.5, handlelength=0.5)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Figure 4\n",
    "\n",
    "#### Step 1: Understanding the graph\n",
    "\n",
    "- the graph corresponds to an horizontal grouped-bar plot;\n",
    "- each group of bars corresponds to a different economic activity and each bar within a group represents a different social media type;\n",
    "- the values displayed show the percentage of enterprises using social media\n",
    "\n",
    "#### Step 2: Data extraction and preparation\n",
    "\n",
    "- dataset code used: `\"isoc_cismt\"`;\n",
    "- the dataframes were created according to the different economic activities and display the percentage values in a specific order: social network first, multi-media sharing websites second, blog or microblogs third and wiki-based tools last;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "#FIGURE 4: data\n",
    "#source: Eurostat API (isoc_cismt)\n",
    "\n",
    "#get data\n",
    "figure4_source = 'isoc_cismt?precision=1&geo=EU28&unit=PC_ENT&indic_is=E_SM1_BLOG&indic_is=E_SM1_CNTSHR&indic_is=E_SM1_SNET&indic_is=E_SM1_WIKI&sizen_r2=10_C10_33&sizen_r2=10_D35_E39&sizen_r2=10_F41_43&sizen_r2=10_G45_47&sizen_r2=10_G47&sizen_r2=10_H49_53&sizen_r2=10_I55&sizen_r2=10_J58_63&sizen_r2=10_L68&sizen_r2=10_M69_74&sizen_r2=10_N77_82&unitLabel=label&time=2019'\n",
    "\n",
    "dataframe_figure4 = client.get_dataset(figure4_source).to_dataframe().set_index('sizen_r2')\n",
    "\n",
    "types_order = ['10_F41_43','10_H49_53','10_D35_E39','10_C10_33','10_L68','10_N77_82','10_M69_74','10_G45_47','10_G47','10_J58_63','10_I55']\n",
    "\n",
    "figure4_network = dataframe_figure4[(dataframe_figure4['indic_is'] == 'E_SM1_SNET')].reindex(types_order)['values'].tolist()\n",
    "\n",
    "figure4_multimedia = dataframe_figure4[(dataframe_figure4['indic_is'] == 'E_SM1_CNTSHR')].reindex(types_order)['values'].tolist()\n",
    "\n",
    "figure4_blog = dataframe_figure4[(dataframe_figure4['indic_is'] == 'E_SM1_BLOG')].reindex(types_order)['values'].tolist()\n",
    "\n",
    "figure4_wiki = dataframe_figure4[(dataframe_figure4['indic_is'] == 'E_SM1_WIKI')].reindex(types_order)['values'].tolist()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Step 3: Plotting\n",
    "\n",
    "- this time, the position of each bar was set based on the y-axis and also according to the length of the array containing the economic activities: using `range(len())` command\n",
    "- once again, for ordering the bars within each group, we represented the bars for the wiki-based tools values in the middle of the yticks and the bars for the types classes sequentially on top, by multiplying the bar's default size and adding it to the original ytick;\n",
    "- when using the plot function, the bar's position parameter is only associated with the y-axis as the barh function is instead used;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <use x=\"282.324219\" xlink:href=\"#DejaVuSans-Bold-105\"/>\r\n",
       "      <use x=\"316.601562\" xlink:href=\"#DejaVuSans-Bold-110\"/>\r\n",
       "      <use x=\"387.792969\" xlink:href=\"#DejaVuSans-Bold-103\"/>\r\n",
       "      <use x=\"459.375\" xlink:href=\"#DejaVuSans-Bold-32\"/>\r\n",
       "      <use x=\"494.189453\" xlink:href=\"#DejaVuSans-Bold-116\"/>\r\n",
       "      <use x=\"541.992188\" xlink:href=\"#DejaVuSans-Bold-111\"/>\r\n",
       "      <use x=\"610.693359\" xlink:href=\"#DejaVuSans-Bold-111\"/>\r\n",
       "      <use x=\"679.394531\" xlink:href=\"#DejaVuSans-Bold-108\"/>\r\n",
       "      <use x=\"713.671875\" xlink:href=\"#DejaVuSans-Bold-115\"/>\r\n",
       "     </g>\r\n",
       "    </g>\r\n",
       "   </g>\r\n",
       "  </g>\r\n",
       " </g>\r\n",
       " <defs>\r\n",
       "  <clipPath id=\"pb70ab094c0\">\r\n",
       "   <rect height=\"221.76\" width=\"334.8\" x=\"310.89875\" y=\"43.162375\"/>\r\n",
       "  </clipPath>\r\n",
       " </defs>\r\n",
       "</svg>\r\n"
      ],
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#FIGURE 4: graph\n",
    "\n",
    "economic_activities = ['Construction','Transport and storage','Electricity, gas, steam and ai conditioning; water supply, sewerage, waste \\n management and remediation activities','Manufacturing','Real estate activities','Administrative and support service activities, excluding travel agency, etc','Professional, scientific and technical activities','Wholesale and retail trade; repair of motor vehicles and motorcycles','Retail trade','Information and communication','Accommodation']\n",
    "\n",
    "media_types = ['Wiki-based knowledge- \\n sharing tools','Enterprise blog \\n or microblogs','Multimedia content- \\n sharing websites','Social networks']\n",
    "\n",
    "colors = ['olivedrab','orange','royalblue','darkorange']\n",
    "\n",
    "r = np.arange(len(economic_activities))\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(6, 4))\n",
    "ax.grid(True, which = 'major', axis = 'x', color ='grey', linestyle = '-', alpha = 0.2) #grey lines\n",
    "sns.despine(top=True, right=True, left=True, bottom=False) #remove spines\n",
    "ax.set_axisbelow(True) #set the grid below the bars\n",
    "barSize = 2.2/len(economic_activities) #width of bars\n",
    "plt.yticks(r + barSize*2, economic_activities, rotation= 0) #y labels\n",
    "ax.set_xlim(0,91)\n",
    "ax.tick_params(axis = 'both', which = 'major', length=0, labelsize = 8) #size of labels in axis\n",
    "plt.xticks(np.arange(0, 91, step=10))\n",
    "\n",
    "#ax.set(yticks=ind + width, yticklabels=df.graph, ylim=[2*width - 1, len(df)])\n",
    "\n",
    "bars_wiki = plt.barh(r, figure4_wiki, align= 'center', color=colors[0], height=barSize, label=media_types[0])\n",
    "\n",
    "bars_blog = plt.barh(r + barSize, figure4_blog, align= 'center', color=colors[1], height=barSize, label=media_types[1])\n",
    "\n",
    "bars_multimedia = plt.barh(r + barSize*2, figure4_multimedia, align= 'center', color=colors[2], height=barSize, label=media_types[2])\n",
    "\n",
    "bars_network = plt.barh(r + barSize*3, figure4_network, align= 'center', color=colors[3], height=barSize, label=media_types[3])\n",
    "\n",
    "#title\n",
    "ax.set_title('Enterprises using social media, by type and economic activity, EU-28, 2019 \\n(% of enterprises)', fontsize=10, fontweight='bold', horizontalalignment = 'left', x = -0.9, y =1.05)\n",
    "\n",
    "#legend\n",
    "leg_snet = Line2D([0],[0], lw=4, color='darkorange', label='Social networks', marker='s')\n",
    "leg_cntshr = Line2D([0],[0], lw=4, color='royalblue', label='Multimedia content- \\n sharing websites', marker='s')\n",
    "leg_blog = Line2D([0],[0], lw=4, color='orange', label='Enterprise blog \\n or microblogs', marker='s')\n",
    "leg_wiki = Line2D([0],[0], lw=4, color='olivedrab', label='Wiki-based knowledge- \\n sharing tools', marker='s')\n",
    "\n",
    "leg = ax.legend(handles=[leg_snet,leg_cntshr,leg_blog,leg_wiki], frameon=False, loc=(-0.55, -.26), ncol=4, prop={'weight':'bold','size':'7'}, labelspacing=0.2, handlelength=0.5)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Purposes of using social media"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "#FIGURE 5: data\n",
    "#source: Eurostat Data Browser (isoc_cismt)\n",
    "\n",
    "figure5_source = 'isoc_cismp?precision=1&geo=EU28&unit=PC_ENT&indic_is=E_SM_PADVERT&indic_is=E_SM_PBPCOLL&indic_is=E_SM_PCUDEV&indic_is=E_SM_PCUQOR&indic_is=E_SM_PEXCHVOK&indic_is=E_SM_PRCR&sizen_r2=10_C10_S951_XK&unitLabel=label&time=2013&time=2015&time=2017&time=2019'\n",
    "\n",
    "dataframe_figure5 = client.get_dataset(figure5_source).to_dataframe()\n",
    "\n",
    "dataframe_figure5_develop = dataframe_figure5.loc[dataframe_figure5['indic_is'] == 'E_SM_PADVERT'].groupby(by = 'time')['values'].sum()\n",
    "dataframe_figure5_obtain = dataframe_figure5.loc[dataframe_figure5['indic_is'] == 'E_SM_PCUQOR'].groupby(by = 'time')['values'].sum()\n",
    "dataframe_figure5_recruit = dataframe_figure5.loc[dataframe_figure5['indic_is'] == 'E_SM_PRCR'].groupby(by = 'time')['values'].sum()\n",
    "dataframe_figure5_exchange = dataframe_figure5.loc[dataframe_figure5['indic_is'] == 'E_SM_PEXCHVOC'].groupby(by = 'time')['values'].sum()\n",
    "dataframe_figure5_involve = dataframe_figure5.loc[dataframe_figure5['indic_is'] == 'E_SM_PCUDEV'].groupby(by = 'time')['values'].sum()\n",
    "dataframe_figure5_collaborate = dataframe_figure5.loc[dataframe_figure5['indic_is'] == 'E_SM_PBPCOLL'].groupby(by = 'time')['values'].sum()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(-0.03, 1.05, 'Enterprises using social media, by purpose of use, EU-28, \\n2013, 2015, 2017 and 2019 \\n(% of enterprises)')"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
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     "metadata": {},
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   ],
   "source": [
    "#FIGURE 5: graph\n",
    "\n",
    "colors = ['darkorange','royalblue','orange','limegreen','yellowgreen','cadetblue']\n",
    "\n",
    "#size of graph\n",
    "fig, ax = plt.subplots(figsize=(10, 4))\n",
    "\n",
    "#grid\n",
    "plt.style.use('default') #aesthetic of sheet\n",
    "ax.grid(True, which = 'major', axis = 'y' , color ='grey', linestyle = '-', alpha = 0.2) #grey lines\n",
    "sns.despine(top=True, right=True, left=True, bottom=False) #remove spines\n",
    "ax.tick_params(axis = 'both',which = 'major' , labelsize = 8) #size of labels in axis\n",
    "ax.xaxis.set_major_locator(ticker.FixedLocator([2013, 2015, 2017, 2019]))\n",
    "\n",
    "#scale of graph\n",
    "plt.ylim(0,51)\n",
    "plt.yticks(np.arange(0, 51, step=5))\n",
    "\n",
    "#plot the data\n",
    "plt.plot(dataframe_figure5_develop, color=colors[0], marker ='s')\n",
    "plt.plot(dataframe_figure5_obtain, color=colors[1], marker ='D', linestyle = 'dashed')\n",
    "plt.plot(dataframe_figure5_recruit, color=colors[2], marker ='^')\n",
    "plt.plot(dataframe_figure5_exchange, color=colors[3], marker ='o')\n",
    "plt.plot(dataframe_figure5_involve, color=colors[4], marker ='|')\n",
    "plt.plot(dataframe_figure5_collaborate, color=colors[5], marker ='x', linestyle = 'dashed')\n",
    "\n",
    "#legend\n",
    "leg_develop = Line2D([0],[0], lw=3, color=colors[0], label='Develop the enterprise\\'s image or market products', marker='s')\n",
    "leg_obtain = Line2D([0],[0], lw=3, color=colors[1], label='Obtain or respond to customers\\' opinions, reviews, questions', marker='D')\n",
    "leg_recruit = Line2D([0],[0], lw=3, color=colors[2], label='Recruit employees', marker='^')\n",
    "leg_exchange = Line2D([0],[0], lw=3, color=colors[3], label='Exchange views, opinions or knowledge within the enterprise', marker='o')\n",
    "leg_involve = Line2D([0],[0], lw=3, color=colors[4], label='Involve customers in development or innovation of goods and services', marker='|')\n",
    "leg_collaborate = Line2D([0],[0], lw=3, color=colors[5], label='Collaborate with business partners or other organisations', marker='x')\n",
    "\n",
    "leg = ax.legend(handles=[leg_develop,leg_obtain,leg_recruit,leg_exchange,leg_involve,leg_collaborate], frameon=False, loc=(0.2, -.5), ncol=1, prop={'weight':'bold','size':'7'}, labelspacing=1, handlelength=1)\n",
    "\n",
    "#title\n",
    "ax.set_title('Enterprises using social media, by purpose of use, EU-28, \\n2013, 2015, 2017 and 2019 \\n(% of enterprises)', fontsize=10, fontweight='bold', horizontalalignment = 'left', x = -0.03, y =1.05)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Purposes of using social media by size of enterprises"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "#FIGURE 6: data\n",
    "#source: Eurostat Data Browser (isoc_cismp)\n",
    "\n",
    "figure6_source = 'isoc_cismp?precision=1&geo=EU28&unit=PC_ENT_SM&indic_is=E_SM_PADVERT&indic_is=E_SM_PBPCOLL&indic_is=E_SM_PCUDEV&indic_is=E_SM_PCUQOR&indic_is=E_SM_PEXCHVOK&indic_is=E_SM_PRCR&sizen_r2=L_C10_S951_XK&sizen_r2=M_C10_S951_XK&sizen_r2=S_C10_S951_XK&unitLabel=label&time=2019'\n",
    "\n",
    "dataframe_figure6 = client.get_dataset(figure6_source).to_dataframe().set_index('indic_is')\n",
    "\n",
    "purpose_order = ['E_SM_PADVERT','E_SM_PCUQOR','E_SM_PRCR','E_SM_PEXCHVOK','E_SM_PCUDEV','E_SM_PBPCOLL']\n",
    "\n",
    "figure6_bars_large = dataframe_figure6[(dataframe_figure6['sizen_r2'] == 'L_C10_S951_XK')].reindex(purpose_order)['values'].tolist()\n",
    "\n",
    "figure6_bars_medium = dataframe_figure6[(dataframe_figure6['sizen_r2'] == 'M_C10_S951_XK')].reindex(purpose_order)['values'].tolist()\n",
    "\n",
    "figure6_bars_small = dataframe_figure6[(dataframe_figure6['sizen_r2'] == 'S_C10_S951_XK')].reindex(purpose_order)['values'].tolist()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      ],
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#FIGURE 6: graph\n",
    "\n",
    "purposes = ['Develop the enterprise\\'s \\n image or market \\n products','Obtain or respond to \\n customers\\' opinions, \\n reviews, questions','Recruit employees','Exchange views, \\n opinions or knowledge \\n within the enterprise','Involve customers in \\n development or \\n innovation of goods and \\n services','Collaborate with \\n business partners or \\n other organisations']\n",
    "\n",
    "sizes = ['large','medium','small']\n",
    "\n",
    "colors = ['tomato', 'royalblue', 'cornflowerblue']\n",
    "\n",
    "r = np.arange(len(purposes))\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(10, 4))\n",
    "ax.grid(True, which = 'major', axis = 'y', color ='grey', linestyle = '-', alpha = 0.2) #grey lines\n",
    "sns.despine(top=True, right=True, left=True, bottom=False) #remove spines\n",
    "ax.set_axisbelow(True) #set the grid below the bars\n",
    "plt.xticks(r, purposes, rotation= 0) #x labels\n",
    "ax.set_ylim(0, 101)\n",
    "ax.tick_params(axis = 'both', which = 'major', labelsize = 6) #size of labels in axis\n",
    "plt.yticks(np.arange(0, 101, step=10))\n",
    "barWidth = 0.2 #width of bars\n",
    "\n",
    "bars_large = plt.bar(r - barWidth, figure6_bars_large, color=colors[0], width=barWidth, label=sizes[0])\n",
    "\n",
    "bars_medium = plt.bar(r, figure6_bars_medium, color=colors[1], width=barWidth, label=sizes[1])\n",
    "\n",
    "bars_small = plt.bar(r + barWidth, figure6_bars_small, color=colors[2], width=barWidth, label=sizes[2])\n",
    "\n",
    "for bars_large, bars_medium, bars_small in zip(bars_large,bars_medium,bars_small):\n",
    "    h_large = bars_large.get_height()\n",
    "    h_medium = bars_medium.get_height()\n",
    "    h_small = bars_small.get_height()\n",
    "    x_large = bars_large.get_x()\n",
    "    x_medium = bars_medium.get_x()\n",
    "    x_small = bars_small.get_x()\n",
    "    plt.text(x_large + barWidth/3, h_large +2, h_large, fontsize='x-small')\n",
    "    plt.text(x_medium + barWidth/3, h_medium +2, h_medium, fontsize='x-small')\n",
    "    plt.text(x_small + barWidth/3, h_small +2, h_small, fontsize='x-small')\n",
    "\n",
    "#title\n",
    "ax.set_title('Enterprises using social media, by purpose of use and size class, EU-28, 2019 \\n(% of enterprises using social media)', fontsize=10, fontweight='bold', horizontalalignment = 'left', x = -0.03, y =1.05)\n",
    "\n",
    "#legend\n",
    "leg_large = Line2D([0],[0], lw=4, color='tomato', label='large', marker='s')\n",
    "leg_medium = Line2D([0],[0], lw=4, color='royalblue', label='medium', marker='s')\n",
    "leg_small = Line2D([0],[0], lw=4, color='cornflowerblue', label='small', marker='s')\n",
    "\n",
    "leg = ax.legend(handles=[leg_large,leg_medium,leg_small], frameon=False, loc=(0.38, -0.26), ncol=3, prop={'weight':'bold','size':'7'}, labelspacing=0.5, handlelength=0.5)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Purposes of using social media by economic activity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "#FIGURE 7: data\n",
    "#source: Eurostat Data Browser (isoc_cismp)\n",
    "\n",
    "figure7_source = 'isoc_cismp?precision=1&geo=EU28&unit=PC_ENT_SM&indic_is=E_SM_PADVERT&indic_is=E_SM_PCUDEV&indic_is=E_SM_PCUQOR&indic_is=E_SM_PRCR&sizen_r2=10_C10_33&sizen_r2=10_D35_E39&sizen_r2=10_F41_43&sizen_r2=10_G45_47&sizen_r2=10_G47&sizen_r2=10_H49_53&sizen_r2=10_I55&sizen_r2=10_J58_63&sizen_r2=10_L68&sizen_r2=10_M69_74&sizen_r2=10_N77_82&unitLabel=label&time=2019'\n",
    "\n",
    "dataframe_figure7 = client.get_dataset(figure7_source).to_dataframe().set_index('sizen_r2')\n",
    "\n",
    "activities_order = ['10_H49_53','10_F41_43','10_D35_E39','10_N77_82','10_M69_74','10_C10_33','10_J58_63','10_L68','10_G45_47','10_G47','10_I55']\n",
    "\n",
    "figure7_involve = dataframe_figure7[(dataframe_figure7['indic_is'] == 'E_SM_PCUDEV')].reindex(activities_order)['values'].tolist()\n",
    "\n",
    "figure7_recruit = dataframe_figure7[(dataframe_figure7['indic_is'] == 'E_SM_PRCR')].reindex(activities_order)['values'].tolist()\n",
    "\n",
    "figure7_obtain = dataframe_figure7[(dataframe_figure7['indic_is'] == 'E_SM_PCUQOR')].reindex(activities_order)['values'].tolist()\n",
    "\n",
    "figure7_develop = dataframe_figure7[(dataframe_figure7['indic_is'] == 'E_SM_PADVERT')].reindex(activities_order)['values'].tolist()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      ],
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#FIGURE 7: graph\n",
    "\n",
    "economic_activities = ['Transport and storage','Construction','Electricity, gas, steam and ai conditioning; water supply, sewerage, \\n waste management and remediation activities','Administrative and support service activities, excluding travel agency, etc','Professional, scientific and technical activities','Manufacturing','Information and communication','Real estate activities','Wholesale and retail trade; repair of motor vehicles and motorcycles','Retail trade','Accommodation']\n",
    "\n",
    "purposes = ['Involve customers in \\n development or \\n innovation of goods and \\n services','Recruit employees','Obtain or respond to \\n customers\\' opinions, \\n reviews, questions','Develop the enterprise\\'s \\n image or market \\n products']\n",
    "\n",
    "colors = ['yellowgreen','orange','royalblue','darkorange']\n",
    "\n",
    "r = np.arange(len(economic_activities))\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(6, 4))\n",
    "ax.grid(True, which = 'major', axis = 'x', color ='grey', linestyle = '-', alpha = 0.2) #grey lines\n",
    "sns.despine(top=True, right=True, left=True, bottom=False) #remove spines\n",
    "ax.set_axisbelow(True) #set the grid below the bars\n",
    "barSize = 2.2/len(economic_activities) #width of bars\n",
    "plt.yticks(r + barSize*2, economic_activities, rotation= 0) #y labels\n",
    "ax.set_xlim(0,101)\n",
    "ax.tick_params(axis = 'both', which = 'major', length=0, labelsize = 8) #size of labels in axis\n",
    "plt.xticks(np.arange(0, 101, step=10))\n",
    "\n",
    "#ax.set(yticks=ind + width, yticklabels=df.graph, ylim=[2*width - 1, len(df)])\n",
    "\n",
    "bars_involve = plt.barh(r, figure7_involve, align= 'center', color=colors[0], height=barSize, label=purposes[0])\n",
    "\n",
    "bars_recruit = plt.barh(r + barSize, figure7_recruit, align= 'center', color=colors[1], height=barSize, label=purposes[1])\n",
    "\n",
    "bars_obtain = plt.barh(r + barSize*2, figure7_obtain, align= 'center', color=colors[2], height=barSize, label=purposes[2])\n",
    "\n",
    "bars_develop = plt.barh(r + barSize*3, figure7_develop, align= 'center', color=colors[3], height=barSize, label=purposes[3])\n",
    "\n",
    "#title\n",
    "ax.set_title('Enterprises using social media, by selected purposes and economic \\nactivity, EU-28, 2019 \\n(% of enterprises using social media)', fontsize=10, fontweight='bold', horizontalalignment = 'left', x = -0.9, y =1.05)\n",
    "\n",
    "#legend\n",
    "leg_develop = Line2D([0],[0], lw=1, color=colors[3], label='Develop the enterprise\\'s image or market \\n products', marker='s')\n",
    "leg_obtain = Line2D([0],[0], lw=1, color=colors[2], label='Obtain or respond to customers\\' opinions, \\n reviews, questions', marker='s')\n",
    "leg_recruit = Line2D([0],[0], lw=1, color=colors[1], label='Recruit employees', marker='s')\n",
    "leg_involve = Line2D([0],[0], lw=1, color=colors[0], label='Involve customers in development or innovation of goods and services', marker='s')\n",
    "\n",
    "leg = ax.legend(handles=[leg_develop,leg_obtain,leg_recruit,leg_involve], frameon=False, loc=(-0.3, -.5), ncol=1, prop={'weight':'bold','size':'7'}, labelspacing=1, handlelength=1)\n"
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   "cell_type": "code",
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   "outputs": [],
   "source": []
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