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142 lines
22 KiB
142 lines
22 KiB
3 years ago
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{
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"cells": [
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{
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"cell_type": "markdown",
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"source": [],
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"metadata": {}
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},
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{
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"cell_type": "markdown",
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"source": [
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"# Assignment: Evaluating Data from a Form\r\n",
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"\r\n",
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"A client has been testing a [small form](index.html) to gather some basic data about their client-base. They have brought their findings to you to validate the data they have gathered. You can open the `index.html` page in a browser to take a look at the form.\r\n",
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"\r\n",
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"You have been provided a [dataset of csv records](../../data/form.csv)that contain entries from the form as well as some basic visualizations.The client pointed out that some of the visualizations look incorrect but they're unsure about how to resolve them. You can explore it in the [assignment notebook](assignment.ipynb).\r\n",
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"\r\n",
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"## Instructions\r\n",
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"\r\n",
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"Use the techniques in this lesson to make recommendations about the form so it captures accurate and consistent information. "
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],
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"metadata": {}
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"source": [
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"!pip install pandas\r\n",
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"!pip install matplotlib"
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],
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"outputs": [],
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"metadata": {}
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"source": [
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"import pandas as pd\r\n",
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"import matplotlib.pyplot as plt\r\n",
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"\r\n",
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"#Loading the dataset\r\n",
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"path = '../../data/form.csv'\r\n",
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"form_df = pd.read_csv(path)\r\n",
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"print(form_df)"
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],
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"outputs": [
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{
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"output_type": "stream",
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"name": "stdout",
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"text": [
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" birth_month state pet\n",
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"0 January NaN Cats\n",
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"1 JAN CA Cats\n",
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"2 Sept Hawaii Dog\n",
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"3 january AK Dog\n",
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"4 July RI Cats\n",
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"5 September California Cats\n",
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"6 April CA Dog\n",
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"7 January California Cats\n",
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"8 November FL Dog\n",
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"9 December Florida Cats\n"
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]
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}
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],
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"metadata": {}
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"source": [
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"form_df['state'].value_counts().plot(kind='bar');\r\n",
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"plt.show()"
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],
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"outputs": [
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{
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"output_type": "display_data",
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"data": {
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"image/png": "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"text/plain": [
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"<Figure size 432x288 with 1 Axes>"
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]
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},
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"metadata": {
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"needs_background": "light"
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}
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}
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],
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"metadata": {}
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"source": [
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"form_df['birth_month'].value_counts().plot(kind='bar');\r\n",
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"plt.show()"
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],
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"outputs": [
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{
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"output_type": "display_data",
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"data": {
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"image/png": "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"text/plain": [
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"<Figure size 432x288 with 1 Axes>"
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]
|
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},
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"metadata": {
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}
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}
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],
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"metadata": {}
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},
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{
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"cell_type": "markdown",
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"source": [],
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"metadata": {}
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}
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],
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"name": "python",
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},
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"pygments_lexer": "ipython3",
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},
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"name": "python3",
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"display_name": "Python 3.9.7 64-bit ('venv': venv)"
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},
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||
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}
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