chore(i18n,learn): processed translations (#45414)
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camperbot
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---
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id: 5e9a093a74c4063ca6f7c14d
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title: Data Analysis Example A
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title: Análisis de datos ejemplo A
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challengeType: 11
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videoId: nVAaxZ34khk
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bilibiliIds:
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aid: 590571151
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bvid: BV1sq4y1f7gr
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cid: 409002372
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dashedName: data-analysis-example-a
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---
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# --description--
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*Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.*
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*En lugar de usar notebooks.ai como se muestra en el vídeo, puedes utilizar Google Colab en su lugar.*
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More resources:
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Más recursos:
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- [Notebooks on GitHub](https://github.com/ine-rmotr-curriculum/FreeCodeCamp-Pandas-Real-Life-Example)
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- [How to open Notebooks from GitHub using Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
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- [Libros de notas en GitHub](https://github.com/ine-rmotr-curriculum/FreeCodeCamp-Pandas-Real-Life-Example)
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- [Cómo abrir libros de notas desde GitHub usando Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
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# --question--
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## --text--
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What does the shape of our dataframe tell us?
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¿Qué nos dice la forma de nuestro marco de datos?
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## --answers--
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The size in gigabytes the dataframe we loaded into memory is.
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El tamaño en gigabytes del marco de datos que cargamos a nuestra memoria es.
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---
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How many rows and columns our dataframe has.
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Cuántas filas y columnas tiene nuestro marco de datos.
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---
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How many rows the source data had before loading.
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Cuántas filas tenían los datos de origen antes de cargar.
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---
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How many columns the source data had before loading.
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Cuántas columnas tenían los datos de origen antes de cargar.
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## --video-solution--
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@ -1,37 +1,41 @@
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---
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id: 5e9a093a74c4063ca6f7c14e
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title: Data Analysis Example B
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title: Análisis de datos ejemplo B
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challengeType: 11
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videoId: 0kJz0q0pvgQ
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bilibiliIds:
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aid: 505593432
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bvid: BV1kg411c7M6
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cid: 409003530
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dashedName: data-analysis-example-b
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---
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# --description--
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*Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.*
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*En lugar de usar notebooks.ai como se muestra en el vídeo, puedes utilizar Google Colab en su lugar.*
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More resources:
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Más recursos:
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- [Notebooks on GitHub](https://github.com/ine-rmotr-curriculum/FreeCodeCamp-Pandas-Real-Life-Example)
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- [How to open Notebooks from GitHub using Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
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- [Notebooks en GitHub](https://github.com/ine-rmotr-curriculum/FreeCodeCamp-Pandas-Real-Life-Example)
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- [Cómo abrir Notebooks desde GitHub usando Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
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# --question--
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## --text--
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What does the `loc` method allow you to do?
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¿Qué permite hacer el método `loc`?
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## --answers--
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Retrieve a subset of rows and columns by supplying integer-location arguments.
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Recuperar un subconjunto de filas y columnas proporcionando argumentos de ubicación en números enteros.
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---
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Access a group of rows and columns by supplying label(s) arguments.
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Acceda a un grupo de filas y columnas proporcionando argumentos de etiqueta(s).
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---
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Returns the first `n` rows based on the integer argument supplied.
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Devuelve las primeras filas `n` basadas en el argumento entero proporcionado.
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## --video-solution--
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@ -1,25 +1,29 @@
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---
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id: 5e9a093a74c4063ca6f7c160
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title: Data Cleaning and Visualizations
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title: Análisis y visualización de datos
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challengeType: 11
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videoId: mHjxzFS5_Z0
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bilibiliIds:
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aid: 933107558
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bvid: BV1KM4y137Ny
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cid: 409019632
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dashedName: data-cleaning-and-visualizations
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---
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# --description--
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*Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.*
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*En vez de usar notebooks.ai como aparece en el video, puedes usar Google Colab.*
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More resources:
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Más recursos:
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- [Notebooks on GitHub](https://github.com/ine-rmotr-curriculum/data-cleaning-rmotr-freecodecamp)
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- [How to open Notebooks from GitHub using Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
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- [Notebooks en GitHub](https://github.com/ine-rmotr-curriculum/data-cleaning-rmotr-freecodecamp)
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- [Como abrir Notebooks desde GitHub usando Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
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# --question--
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## --text--
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When using Matplotlib's global API, what does the order of numbers mean here?
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Al utilizar la API global de Matplotlib, ¿qué significa aquí el orden de los números?
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```py
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plt.subplot(1, 2, 1)
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@ -27,15 +31,15 @@ plt.subplot(1, 2, 1)
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## --answers--
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My figure will have one column, two rows, and I am going to start drawing in the first (left) plot.
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Mi figura tendrá una columna, dos filas y voy a empezar dibujando en la primera de la izquierda.
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---
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I am going to start drawing in the first (left) plot, my figure will have two rows, and my figure will have one column.
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Voy a empezar a dibujar en la primera trama (izquierda), mi figura tendrá dos filas y mi figura tendrá una columna.
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---
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My figure will have one row, two columns, and I am going to start drawing in the first (left) plot.
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Mi figura tendrá una fila, dos columnas, y voy a empezar a dibujar en la primera trama (izquierda).
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## --video-solution--
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