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6 changes: 6 additions & 0 deletions .ipynb_checkpoints/Untitled-checkpoint.ipynb
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{
"cells": [],
"metadata": {},
"nbformat": 4,
"nbformat_minor": 5
}
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171 changes: 171 additions & 0 deletions your-code/.ipynb_checkpoints/main-checkpoint.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### 1. Import pandas library"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"kkkk"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### 2. Import users table:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### 3. Rename Id column to userId"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### 4. Import posts table:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### 5. Rename Id column to postId and OwnerUserId to userId"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### 6. Define new dataframes for users and posts with the following selected columns:\n",
" **users columns**: userId, Reputation,Views,UpVotes,DownVotes\n",
" **posts columns**: postId, Score,userId,ViewCount,CommentCount"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### 7. Merge both dataframes, users and posts. \n",
"You will need to make a [merge](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.merge.html) of posts and users dataframes."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### 8. How many missing values do you have in your merged dataframe? On which columns?"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### 9. You will need to make something with missing values. Will you clean or filling them? Explain. \n",
"**Remember** to check the results of your code before passing to the next step"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### 10. Adjust the data types in order to avoid future issues. Which ones should be changed? "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
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"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
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"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
526,849 changes: 526,849 additions & 0 deletions your-code/datasets/posts_table.csv

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66,797 changes: 66,797 additions & 0 deletions your-code/datasets/users_table.csv

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