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traffic-data-cleaning.ipynb

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"import sys"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# The original csv with all the data was too big to upload to Github, so the original data was downloaded locally and not pushed to Github. The data can be downloaded and found here: https://data.bts.gov/Research-and-Statistics/Trips-by-Distance/w96p-f2qv"
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]
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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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"national_and_state = df.drop(index=df[df['Level'] == 'County'].index)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Uploading the state and national data as a csv."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 25,
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"df['County Name'].value_counts()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Subsetting the dataframe to get only Los Angeles County data. "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"la_data = df[df['County Name'] == 'Los Angeles County']"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Reformatting the Date Column to be ISO 8601 format."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"la_data.info()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Converting the Date column to datetime data type."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,

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