In [ ]: In [ ]: In [ ]: In [ ]: In [ ]: In [ ]: In [ ]: Assign a name to this data (whatever name you want) Take a look at the first 15 rows returns statistics about the numerical columns in a dataset Get all the geographical locations whose geography_type is town Get the geographical location that has the max percentage of 'less_than_high_school_graduate' Get the average percentage of bachelor_s_degree_or_higher Make a countplot using seaborn (x = 'geography_type') Make a barplot using seaborn (assign geography as x axis, assign some_college_or_associate_s_degree as y axis) feel free to use plt.xticks(rotation=70) and plt.tight_layout() if you think location names are squeezing together

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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please code this for python 

 

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Assign a name to this data (whatever name you want)
Take a look at the first 15 rows
returns statistics about the numerical columns in a dataset
Get all the geographical locations whose geography_type is town
Get the geographical location that has the max percentage of 'less_than_high_school_graduate'
Get the average percentage of bachelor_s_degree_or_higher
Make a countplot using seaborn (x = 'geography_type')
Make a barplot using seaborn (assign geography as x axis, assign some_college_or_associate_s_degree as y axis) feel free to use plt.xticks (rotation=70) and
plt.tight_layout() if you think location names are squeezing together
Transcribed Image Text:In [ ]: In [ ]: In [ ]: In [ ]: In [ ]: In [ ]: In [ ]: In [ ]: Assign a name to this data (whatever name you want) Take a look at the first 15 rows returns statistics about the numerical columns in a dataset Get all the geographical locations whose geography_type is town Get the geographical location that has the max percentage of 'less_than_high_school_graduate' Get the average percentage of bachelor_s_degree_or_higher Make a countplot using seaborn (x = 'geography_type') Make a barplot using seaborn (assign geography as x axis, assign some_college_or_associate_s_degree as y axis) feel free to use plt.xticks (rotation=70) and plt.tight_layout() if you think location names are squeezing together
In [1]: #Numbers are percentage. We'll use Pandas and Matplotlib/Seaborn to analyze the data.
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This dataset contains data about the highest grade completed by residents of San Mateo County, California by city. Grade levels include less than high school
graduate, high school graduate, some college or associate's degree, and bachelor's degree or higher. This data was extracted from the United States Cenus
Bureau.
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Import all related packages
Get the data. Use this data
pd.read_json("https://data.smcgov.org/resource/mb6a-xn89.json").
Assign a name to this data (whatever name you want)
Take a look at the first 15 rows
returns statistics about the numerical columns in a dataset
Get all the geographical locations whose geography_type is town
Get the geographical location that has the max percentage of 'less_than_high_school_graduate'
Transcribed Image Text:In [1]: #Numbers are percentage. We'll use Pandas and Matplotlib/Seaborn to analyze the data. In [ ]: In [ ]: In [ ]: In [ ]: This dataset contains data about the highest grade completed by residents of San Mateo County, California by city. Grade levels include less than high school graduate, high school graduate, some college or associate's degree, and bachelor's degree or higher. This data was extracted from the United States Cenus Bureau. In [ ]: Import all related packages Get the data. Use this data pd.read_json("https://data.smcgov.org/resource/mb6a-xn89.json"). Assign a name to this data (whatever name you want) Take a look at the first 15 rows returns statistics about the numerical columns in a dataset Get all the geographical locations whose geography_type is town Get the geographical location that has the max percentage of 'less_than_high_school_graduate'
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