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                "Spatial Joins"
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                "Joins Espaciales"
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                "Spatial joins are the bread-and-butter of spatial databases.  They allow you to combine information from different tables by using spatial relationships as the join key.  Much of what we think of as \"standard GIS analysis\" can be expressed as spatial joins."
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                "Las uniones espaciales son el pan de cada día de las bases de datos espaciales. Permiten combinar información de diferentes tablas usando relaciones espaciales como la clave de unión. Gran parte de lo que consideramos \"análisis GIS estándar\" puede expresarse como uniones espaciales."
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                "In the previous section, we explored spatial relationships using a two-step process: first we extracted a subway station point for 'Broad St'; then, we used that point to ask further questions such as \"what neighborhood is the 'Broad St' station in?\""
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                "En la sección anterior, exploramos relaciones espaciales usando un proceso de dos pasos: primero extrajimos un punto de estación de metro para 'Broad St'; luego, usamos ese punto para hacer más preguntas como \"¿en qué vecindario está la estación 'Broad St'?\""
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                "Using a spatial join, we can answer the question in one step, retrieving information about the subway station and the neighborhood that contains it:"
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                "Usando una unión espacial, podemos responder la pregunta en un solo paso, recuperando información sobre la estación de metro y el vecindario que la contiene:"
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                "We could have joined every subway station to its containing neighborhood, but in this case we wanted information about just one.  Any function that provides a true/false relationship between two tables can be used to drive a spatial join, but the most commonly used ones are: :command:`ST_Intersects`, :command:`ST_Contains`, and :command:`ST_DWithin`."
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            "source": [
                "Join and Summarize"
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                "Unir y resumir"
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            "source": [
                "The combination of a ``JOIN`` with a ``GROUP BY`` provides the kind of analysis that is usually done in a GIS system."
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                "La combinación de un ``JOIN`` con un ``GROUP BY`` proporciona el tipo de análisis que usualmente se hace en un SIG."
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            "source": [
                "For example: **\"What is the population and racial make-up of the neighborhoods of Manhattan?\"** Here we have a question that combines information from about population from the census with the boundaries of neighborhoods, with a restriction to just one borough of Manhattan."
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                "Por ejemplo: **\"¿Cuál es la población y la composición racial de los vecindarios de Manhattan?\"** Aquí tenemos una pregunta que combina información de la población del censo con los límites de los vecindarios, con una restricción a solo un distrito de Manhattan."
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            "source": [
                "What's going on here? Notionally (the actual evaluation order is optimized under the covers by the database) this is what happens:"
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                "¿Qué está pasando aquí? En teoría (el orden de evaluación real es optimizado internamente por la base de datos) esto es lo que ocurre:"
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                "The ``JOIN`` clause creates a virtual table that includes columns from both the neighborhoods and census tables."
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                "La cláusula ``JOIN`` crea una tabla virtual que incluye columnas tanto de la tabla de vecindarios como de la tabla del censo."
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                "The ``WHERE`` clause filters our virtual table to just rows in Manhattan."
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                "La cláusula ``WHERE`` filtra nuestra tabla virtual a solo filas en Manhattan."
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                "The remaining rows are grouped by the neighborhood name and fed through the aggregation function to :command:`Sum()` the population values."
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                "Las filas restantes se agrupan por el nombre del vecindario y se procesan a través de la función de agregación :command:`Sum()` de los valores de población."
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            "source": [
                "After a little arithmetic and formatting (e.g., ``GROUP BY``, ``ORDER BY``) on the final numbers, our query spits out the percentages."
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                "Después de un poco de aritmética y formato (por ejemplo, ``GROUP BY``, ``ORDER BY``) sobre los números finales, nuestra consulta arroja los porcentajes."
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            "source": [
                "The ``JOIN`` clause combines two ``FROM`` items.  By default, we are using an ``INNER JOIN``, but there are four other types of joins. For further information see the `join_type <http://www.postgresql.org/docs/9.1/interactive/sql-select.html#SQL-FROM>`_ definition in the PostgreSQL documentation."
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                "La cláusula ``JOIN`` combina dos elementos de ``FROM``. Por defecto, estamos usando un ``INNER JOIN``, pero hay otros cuatro tipos de joins. Para más información ver la definición de `join_type <http://www.postgresql.org/docs/9.1/interactive/sql-select.html#SQL-FROM>`_ en la documentación de PostgreSQL."
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                "We can also use distance tests as a join key, to create summarized \"all items within a radius\" queries. Let's explore the racial geography of New York using distance queries."
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                "También podemos usar pruebas de distancia como clave de unión, para crear consultas resumidas de \"todos los elementos dentro de un radio\". Exploremos la geografía racial de Nueva York usando consultas de distancia."
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                "First, let's get the baseline racial make-up of the city."
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            "source": [
                "So, of the 8M people in New York, about 44% are recorded as \"white\" and 26% are recorded as \"black\"."
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                "Así, de los 8 millones de personas en Nueva York, aproximadamente 44% están registradas como \"blancas\" y 26% están registradas como \"negras\"."
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            "source": [
                "Duke Ellington once sang that \"You / must take the A-train / To / go to Sugar Hill way up in Harlem.\" As we saw earlier, Harlem has far and away the highest African-American population in Manhattan (80.5%). Is the same true of Duke's A-train?"
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                "Duke Ellington una vez cantó \"You / must take the A-train / To / go to Sugar Hill way up in Harlem.\" Como vimos antes, Harlem tiene por mucho la mayor población afroamericana en Manhattan (80.5%). ¿Es lo mismo cierto para el tren A de Duke?"
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            "source": [
                "First, note that the contents of the ``nyc_subway_stations`` table ``routes`` field is what we are interested in to find the A-train. The values in there are a little complex."
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                "Primero, nota que el contenido del campo ``routes`` de la tabla ``nyc_subway_stations`` es lo que nos interesa para encontrar el tren A. Los valores allí son un poco complejos."
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            "source": [
                "The ``DISTINCT`` keyword eliminates duplicate rows from the result.  Without the ``DISTINCT`` keyword, the query above identifies 491 results instead of 73."
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            "source": [
                "So to find the A-train, we will want any row in ``routes`` that has an 'A' in it. We can do this a number of ways, but today we will use the fact that :command:`strpos(routes,'A')` will return a non-zero number only if 'A' is in the ``routes`` field."
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                "Así que para encontrar el tren A, queremos cualquier fila en ``routes`` que tenga una 'A'. Podemos hacerlo de varias formas, pero hoy usaremos el hecho de que :command:`strpos(routes,'A')` devolverá un número distinto de cero solo si 'A' está en el campo ``routes``."
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            "source": [
                "Let's summarize the racial make-up of within 200 meters of the A-train line."
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                "Resumamos la composición racial dentro de 200 metros de la línea del tren A."
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            "source": [
                "So the racial make-up along the A-train isn't radically different from the make-up of New York City as a whole."
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                "Así que la composición racial a lo largo del tren A no es radicalmente diferente de la composición de la ciudad de Nueva York en su conjunto."
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            "source": [
                "Advanced Join"
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                "Joins avanzados"
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            "source": [
                "In the last section we saw that the A-train didn't serve a population that differed much from the racial make-up of the rest of the city. Are there any trains that have a non-average racial make-up?"
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                "En la última sección vimos que el tren A no servía a una población que difiriera mucho de la composición racial del resto de la ciudad. ¿Hay algunos trenes que tengan una composición racial no promedio?"
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            "source": [
                "To answer that question, we'll add another join to our query, so that we can simultaneously calculate the make-up of many subway lines at once. To do that, we'll need to create a new table that enumerates all the lines we want to summarize."
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                "Para responder a esa pregunta, añadiremos otra unión a nuestra consulta, de modo que podamos calcular simultáneamente la composición de muchas líneas de metro a la vez. Para hacer eso, necesitaremos crear una nueva tabla que enumere todas las líneas que queremos resumir."
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            "source": [
                "Now we can join the table of subway lines onto our original query."
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                "Ahora podemos unir la tabla de líneas de metro a nuestra consulta original."
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                "As before, the joins create a virtual table of all the possible combinations available within the constraints of the ``JOIN ON`` restrictions, and those rows are then fed into a ``GROUP`` summary. The spatial magic is in the ``ST_DWithin`` function, that ensures only census blocks close to the appropriate subway stations are included in the calculation."
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