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🙂 How did the Prospect Park areas price index change month-over-month in October 2017?

GenAI

😎 RAG from Cocoon: Putting the question in context using Cocoon's ER story...

- Description: City-wide indices reveal overall NYC real estate trends.
  Name: NYCOverallRealEstateIndices
  Type: Group
- Description: Borough-specific indices show varying real estate performance.
  Name: NYCBoroughRealEstateIndices
  Type: Group
- Description: Neighborhood indices highlight local real estate value shifts.
  Name: NYCHousingPriceIndices
  Type: Group
- Description: Detailed metrics expose nuanced market behavior (2010-2018).
  Name: NYCRealEstateMarketMetrics
  Type: Group

🤓 We've found the related relations: NYCBoroughRealEstateIndices, NYCHousingPriceIndices, NYCRealEstateMarketMetrics

Story behind the relationships (oval for entity, box for relation, octagon for table group))

[NYCOverallRealEstateIndices]: City-wide indices reveal overall NYC real estate trends.
[NYCBoroughRealEstateIndices]: Borough-specific indices show varying real estate performance.
[NYCHousingPriceIndices]: Neighborhood indices highlight local real estate value shifts.
[NYCRealEstateMarketMetrics]: Detailed metrics expose nuanced market behavior (2010-2018).

Reasoning: The question is asking about the price index change for the Prospect Park area in October 2017, specifically the month-over-month change. In the story, it is asking for detailed, localized real estate information about a specific neighborhood (Prospect Park) at a particular point in time (October 2017). This requires granular data that can show month-to-month changes in real estate prices for individual neighborhoods.

GenAI

😎 RAG from Cocoon: Checking out all the related tables Cocoon set up...

- partitons: The data for NYCRealEstateMarketMetrics is partitioned into 43 tables
  table_names:
  - stg_A1_totalInventory_All
  - stg_A3_medianAskingPrice_All
  - stg_A5_recordedSalesVolume_All
  - stg_A6_medianSalePrice_All
  - stg_A7_saleListRatio_All
  - stg_A8_priceCutShare_All
  - stg_A9_daysOnMarket_All
  - stg_B1_totalInventory_Condo
  - stg_B3_medianAskingPrice_Condo
  - stg_B5_recordedSalesVolume_Condo
  - stg_B6_medianSalePrice_Condo
  - stg_B7_saleListRatio_Condo
  - stg_B8_priceCutShare_Condo
  - stg_B9_daysOnMarket_Condo
  - stg_C1_totalInventory_Coop
  - stg_C3_medianAskingPrice_Coop
  - stg_C5_recordedSalesVolume_Coop
  - stg_C6_medianSalePrice_Coop
  - stg_C7_saleListRatio_Coop
  - stg_C8_priceCutShare_Coop
  - stg_C9_daysOnMarket_Coop
  - stg_D1_totalInventory_Sfr
  - stg_D3_medianAskingPrice_Sfr
  - stg_D5_recordedSalesVolume_Sfr
  - stg_D6_medianSalePrice_Sfr
  - stg_D7_saleListRatio_Sfr
  - stg_D8_priceCutShare_Sfr
  - stg_D9_daysOnMarket_Sfr
  - stg_E1_rentalInventory_All
  - stg_E2_medianAskingRent_All
  - stg_E3_discountShare_All
  - stg_F1_rentalInventory_Studio
  - stg_F2_medianAskingRent_Studio
  - stg_F3_discountShare_Studio
  - stg_G1_rentalInventory_OneBd
  - stg_G2_medianAskingRent_OneBd
  - stg_G3_discountShare_OneBd
  - stg_H1_rentalInventory_TwoBd
  - stg_H2_medianAskingRent_TwoBd
  - stg_H3_discountShare_TwoBd
  - stg_I1_rentalInventory_ThreePlusBd
  - stg_I2_medianAskingRent_ThreePlusBd
  - stg_I3_discountShare_ThreePlusBd
  table_desc: The table shows real estate data for New York City. It includes metrics
    like inventory (the number of rental listings), prices cut (the exact middle price
    cut as a percentage of total asking price), Sale-to-List Price Ratio (the final
    recorded sales price of a home divided by its initial asking price), etc. Data
    is split by property type (all, condo, coop, SFR). It covers rental data too.
    Metrics are tracked monthly from 2010 to 2018. Areas are divided into Manhattan
    submarkets.
  attributes:
  - Area
  - Borough
  - AreaType
  - date_2010_01
  - date_2010_02
  - date_2010_03
  - date_2010_04
  - date_2010_05
  - date_2010_06
  - date_2010_07
  - date_2010_08
  - date_2010_09
  - date_2010_10
  - date_2010_11
  - date_2010_12
  - date_2011_01
  - date_2011_02
  - date_2011_03
  - date_2011_04
  - date_2011_05
  - date_2011_06
  - date_2011_07
  - date_2011_08
  - date_2011_09
  - date_2011_10
  - date_2011_11
  - date_2011_12
  - date_2012_01
  - date_2012_02
  - date_2012_03
  - date_2012_04
  - date_2012_05
  - date_2012_06
  - date_2012_07
  - date_2012_08
  - date_2012_09
  - date_2012_10
  - date_2012_11
  - date_2012_12
  - date_2013_01
  - date_2013_02
  - date_2013_03
  - date_2013_04
  - date_2013_05
  - date_2013_06
  - date_2013_07
  - date_2013_08
  - date_2013_09
  - date_2013_10
  - date_2013_11
  - date_2013_12
  - date_2014_01
  - date_2014_02
  - date_2014_03
  - date_2014_04
  - date_2014_05
  - date_2014_06
  - date_2014_07
  - date_2014_08
  - date_2014_09
  - date_2014_10
  - date_2014_11
  - date_2014_12
  - date_2015_01
  - date_2015_02
  - date_2015_03
  - date_2015_04
  - date_2015_05
  - date_2015_06
  - date_2015_07
  - date_2015_08
  - date_2015_09
  - date_2015_10
  - date_2015_11
  - date_2015_12
  - date_2016_01
  - date_2016_02
  - date_2016_03
  - date_2016_04
  - date_2016_05
  - date_2016_06
  - date_2016_07
  - date_2016_08
  - date_2016_09
  - date_2016_10
  - date_2016_11
  - date_2016_12
  - date_2017_01
  - date_2017_02
  - date_2017_03
  - date_2017_04
  - date_2017_05
  - date_2017_06
  - date_2017_07
  - date_2017_08
  - date_2017_09
  - date_2017_10
  - date_2017_11
  - date_2017_12
  - date_2018_01
  - date_2018_02
  - date_2018_03
  - date_2018_04
  - date_2018_05
  - date_2018_06
  - date_2018_07
  - date_2018_08
  - date_2018_09
- partitons: The data for BrooklynRealEstateIndices is partitioned into 2 tables
  table_names:
  - stg_priceIndex_condos_co_ops_homes_Brooklyn_2018_09
  - stg_rentIndex_condos_co_ops_homes_Brooklyn_2018_09
  table_desc: The table shows price indices and rent indices for Brooklyn. Each index
    uses a repeat-sales method of comparing the sales prices of the same properties
    since January 1995 in Manhattan and January 2005 in Brooklyn and Queens. It covers
    condos, co-ops, and homes. Data is split into quintiles. Monthly and yearly changes
    are included. The table starts from 1995 but has missing early data. It likely
    continues to 2018.
  attributes:
  - date_
  - brooklyn_price_index
  - brooklyn_q1_price_index
  - brooklyn_q2_price_index
  - brooklyn_q3_price_index
  - brooklyn_q4_price_index
  - brooklyn_q5_price_index
  - brooklyn_price_index_mom
  - brooklyn_q1_price_index_mom
  - brooklyn_q2_price_index_mom
  - brooklyn_q3_price_index_mom
  - brooklyn_q4_price_index_mom
  - brooklyn_q5_price_index_mom
  - brooklyn_price_index_yoy
  - brooklyn_q1_price_index_yoy
  - brooklyn_q2_price_index_yoy
  - brooklyn_q3_price_index_yoy
  - brooklyn_q4_price_index_yoy
  - brooklyn_q5_price_index_yoy
- partitons: The data for QueensRealEstateIndices is partitioned into 2 tables
  table_names:
  - stg_priceIndex_condos_co_ops_homes_Queens_2018_09
  - stg_rentIndex_condos_co_ops_homes_Queens_2018_09
  table_desc: The table shows price indices for Queens real estate. It includes data
    for all properties and five quintiles. The table has monthly and yearly changes.
    It covers condos, co-ops, and homes. The data starts from 1995. The rent index
    partition likely has a similar structure.
  attributes:
  - date_
  - queens_all_index
  - queens_q1_index
  - queens_q2_index
  - queens_q3_index
  - queens_q4_index
  - queens_q5_index
  - queens_all_mom_change
  - queens_q1_mom_change
  - queens_q2_mom_change
  - queens_q3_mom_change
  - queens_q4_mom_change
  - queens_q5_mom_change
  - queens_all_yoy_change
  - queens_q1_yoy_change
  - queens_q2_yoy_change
  - queens_q3_yoy_change
  - queens_q4_yoy_change
  - queens_q5_yoy_change
- partitons: The data for NYCHousingPriceIndices is partitioned into 15 tables
  table_names:
  - stg_priceIndex_condos_co_ops_homes_All_Downtown_2018_09
  - stg_priceIndex_condos_co_ops_homes_All_Midtown_2018_09
  - stg_priceIndex_condos_co_ops_homes_All_Upper_East_Side_2018_09
  - stg_priceIndex_condos_co_ops_homes_All_Upper_Manhattan_2018_09
  - stg_priceIndex_condos_co_ops_homes_All_Upper_West_Side_2018_09
  - stg_priceIndex_condos_co_ops_homes_Central_Queens_2018_09
  - stg_priceIndex_condos_co_ops_homes_East_Brooklyn_2018_09
  - stg_priceIndex_condos_co_ops_homes_Northeast_Queens_2018_09
  - stg_priceIndex_condos_co_ops_homes_Northwest_Brooklyn_2018_09
  - stg_priceIndex_condos_co_ops_homes_Northwest_Queens_2018_09
  - stg_priceIndex_condos_co_ops_homes_North_Brooklyn_2018_09
  - stg_priceIndex_condos_co_ops_homes_Prospect_Park_2018_09
  - stg_priceIndex_condos_co_ops_homes_South_Brooklyn_2018_09
  - stg_priceIndex_condos_co_ops_homes_South_Queens_2018_09
  - stg_priceIndex_condos_co_ops_homes_The_Rockaways_2018_09
  table_desc: The table shows price indices for housing in NYC boroughs. Each index
    uses a repeat-sales method of comparing the sales prices of the same properties.
    It includes data for Downtown, Midtown, Upper East Side, and other neighborhoods.
    Each partition has columns for date, sales price, month-over-month change, and
    year-over-year change. The data spans from 1995 to at least 2018. It tracks housing
    market trends across various NYC areas.
  attributes:
  - date_
  - average_sales_price
  - month_over_month_change
  - year_over_year_change
- partitons: The data for ManhattanRealEstateIndices2018 is partitioned into 2 tables
  table_names:
  - stg_priceIndex_condos_co_ops_homes_Manhattan_2018_09
  - stg_rentIndex_condos_co_ops_homes_Manhattan_2018_09
  table_desc: The table shows price indices for Manhattan properties. Each index uses
    a repeat-sales method of comparing the sales prices of the same properties since
    January 1995 in Manhattan and January 2005. Values are given for different dates.
    Monthly and yearly changes are calculated. The rent index partition likely has
    a similar structure for rental prices.
  attributes:
  - date_
  - manhattan_price_index
  - manhattan_q1_price_index
  - manhattan_q2_price_index
  - manhattan_q3_price_index
  - manhattan_q4_price_index
  - manhattan_q5_price_index
  - manhattan_price_index_mom
  - manhattan_q1_price_index_mom
  - manhattan_q2_price_index_mom
  - manhattan_q3_price_index_mom
  - manhattan_q4_price_index_mom
  - manhattan_q5_price_index_mom
  - manhattan_price_index_yoy
  - manhattan_q1_price_index_yoy
  - manhattan_q2_price_index_yoy
  - manhattan_q3_price_index_yoy
  - manhattan_q4_price_index_yoy
  - manhattan_q5_price_index_yoy

🤓 We've identified the related tables: stg_priceIndex_condos_co_ops_homes_Prospect_Park_2018_09

🧠 Explanation: The available data appears to be sufficient to answer the business question "How did the Prospect Park areas price index change month-over-month in October 2017?". The NYCHousingPriceIndices dataset contains a table specifically for Prospect Park area (stg_priceIndex_condos_co_ops_homes_Prospect_Park_2018_09). This table includes monthly data on price indices, including month-over-month changes. The data spans from 1995 to at least 2018, which covers the period of interest (October 2017).
💡 Instruction to write SQL: 1. Select the relevant table: stg_priceIndex_condos_co_ops_homes_Prospect_Park_2018_09 2. Filter the data to focus on October 2017 3. Select the month-over-month change column 4. No joins or complex aggregations are needed as the required information is present in a single table The approach would involve: - Using the 'date_' column to filter for October 2017 - Selecting the 'month_over_month_change' column for the filtered row This straightforward query should provide the month-over-month change in the price index for the Prospect Park area in October 2017.

GenAI

😎 RAG from Cocoon: Looking at how tables connect, thanks to Cocoon's key info...

stg_priceIndex_condos_co_ops_homes_Prospect_Park_2018_09:
  foreign_keys: null
  primary_key: null
  time_keys:
  - date_

🤓 We've planned the join: To execute the SQL, no joins are needed. The query can be performed on a single table: 'stg_priceIndex_condos_co_ops_homes_Prospect_Park_2018_09'. The 'date_' column will be used to filter for October 2017, and the 'month_over_month_change' column will be selected for the resulting row.

GenAI

😎 RAG from Cocoon: Diving into column details Cocoon prepared... getting a bit technical here!

stg_priceIndex_condos_co_ops_homes_Prospect_Park_2018_09:
- name: date_
  description: Date of the housing price data
- name: month_over_month_change
  description: Month-over-month change in housing prices

🤔 Reasoning for column selection: Based on the SQL approach and join description provided, we only need to work with a single table: 'stg_priceIndex_condos_co_ops_homes_Prospect_Park_2018_09'. The approach requires filtering the data for October 2017 and selecting the month-over-month change. Therefore, we need: 1. The 'date_' column for filtering the specific month (October 2017). 2. The 'month_over_month_change' column for the final output. No joins are required, and no complex calculations are needed as the month-over-month change is already available in the table.

GenAI

😊 We have written the SQL:

SELECT month_over_month_change
FROM stg_priceIndex_condos_co_ops_homes_Prospect_Park_2018_09
WHERE date_ LIKE '2017-10%'
LIMIT 1

GenAI

🤓 RAG from Cocoon: Beware! The following are unaddressed data quality issues that may compromise the results:

❓ stg_priceIndex_condos_co_ops_homes_Prospect_Park_2018_09[month_over_month_change] has Missing Value: No previous month data for first month's entry.