{
"nbformat": 4,
"nbformat_minor": 0,
"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": "3.7.3"
},
"colab": {
"name": "Programming Languages (complete).ipynb",
"provenance": []
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "MAAKxOwsGxuj",
"colab_type": "text"
},
"source": [
"## Get the Data\n",
"\n",
"Either use the provided .csv file or (optionally) get fresh (the freshest?) data from running an SQL query on StackExchange: \n",
"\n",
"Follow this link to run the query from [StackExchange](https://data.stackexchange.com/stackoverflow/query/675441/popular-programming-languages-per-over-time-eversql-com) to get your own .csv file\n",
"\n",
"\n",
"select dateadd(month, datediff(month, 0, q.CreationDate), 0) m, TagName, count(*)\n",
"from PostTags pt\n",
"join Posts q on q.Id=pt.PostId\n",
"join Tags t on t.Id=pt.TagId\n",
"where TagName in ('java','c','c++','python','c#','javascript','assembly','php','perl','ruby','visual basic','swift','r','object-c','scratch','go','swift','delphi')\n",
"and q.CreationDate < dateadd(month, datediff(month, 0, getdate()), 0)\n",
"group by dateadd(month, datediff(month, 0, q.CreationDate), 0), TagName\n",
"order by dateadd(month, datediff(month, 0, q.CreationDate), 0)\n",
""
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "u5KcSXt1Gxuk",
"colab_type": "text"
},
"source": [
"## Import Statements"
]
},
{
"cell_type": "code",
"metadata": {
"id": "Ru4Wq-pXGxuk",
"colab_type": "code",
"colab": {}
},
"source": [
"import pandas as pd\n",
"import matplotlib.pyplot as plt"
],
"execution_count": 30,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "xEP6beuEGxun",
"colab_type": "text"
},
"source": [
"## Data Exploration"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "w3Q75B4CGxun",
"colab_type": "text"
},
"source": [
"**Challenge**: Read the .csv file and store it in a Pandas dataframe"
]
},
{
"cell_type": "code",
"metadata": {
"id": "Bm7hQtEGIiri",
"colab_type": "code",
"colab": {}
},
"source": [
"df = pd.read_csv('QueryResults.csv', names=['DATE', 'TAG', 'POSTS'], header=0)"
],
"execution_count": 31,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "x2WnDM75Gxup",
"colab_type": "text"
},
"source": [
"**Challenge**: Examine the first 5 rows and the last 5 rows of the of the dataframe"
]
},
{
"cell_type": "code",
"metadata": {
"id": "50oqpUxVIiJf",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 198
},
"outputId": "c78f0565-5f14-4d0a-c286-1cab57ce10a9"
},
"source": [
"df.head()"
],
"execution_count": 32,
"outputs": [
{
"output_type": "execute_result",
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