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chore(i18n,curriculum): update translations (#43033)

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curriculum/challenges/portuguese/08-data-analysis-with-python/data-analysis-with-python-course/data-analysis-example-a.md
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---
id: 5e9a093a74c4063ca6f7c14d
title: Data Analysis Example A
title: Exemplo de análise de dados A
challengeType: 11
videoId: nVAaxZ34khk
dashedName: data-analysis-example-a
@ -8,34 +8,34 @@ dashedName: data-analysis-example-a
# --description--
*Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.*
*Ao invés de usar notebooks.ai como foi mostrado no vídeo, você pode usar o Google Colab como substituto.*
More resources:
Mais recursos:
- [Notebooks on GitHub](https://github.com/ine-rmotr-curriculum/FreeCodeCamp-Pandas-Real-Life-Example)
- [How to open Notebooks from GitHub using Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
- [Notebooks no GitHub](https://github.com/ine-rmotr-curriculum/FreeCodeCamp-Pandas-Real-Life-Example)
- [Como abrir notebooks do GitHub usando o Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
# --question--
## --text--
What does the shape of our dataframe tell us?
O que nos diz a forma do nosso dataframe?
## --answers--
The size in gigabytes the dataframe we loaded into memory is.
O tamanho em gigabytes do dataframe que carregamos na memória.
---
How many rows and columns our dataframe has.
Quantas linhas e colunas o dataframe tem.
---
How many rows the source data had before loading.
Quantas linhas os dados de origem tinham antes de serem carregados.
---
How many columns the source data had before loading.
Quantas colunas os dados de origem tinham antes de serem carregados.
## --video-solution--

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curriculum/challenges/portuguese/08-data-analysis-with-python/data-analysis-with-python-course/data-analysis-example-b.md
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---
id: 5e9a093a74c4063ca6f7c14e
title: Data Analysis Example B
title: Exemplo de análise de dados B
challengeType: 11
videoId: 0kJz0q0pvgQ
dashedName: data-analysis-example-b
@ -8,30 +8,30 @@ dashedName: data-analysis-example-b
# --description--
*Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.*
*Ao invés de usar notebooks.ai como foi mostrado no vídeo, você pode usar o Google Colab como substituto.*
More resources:
Mais recursos:
- [Notebooks on GitHub](https://github.com/ine-rmotr-curriculum/FreeCodeCamp-Pandas-Real-Life-Example)
- [How to open Notebooks from GitHub using Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
- [Notebooks no GitHub](https://github.com/ine-rmotr-curriculum/FreeCodeCamp-Pandas-Real-Life-Example)
- [Como abrir notebooks do GitHub usando o Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
# --question--
## --text--
What does the `loc` method allow you to do?
O que o método `loc` permite que você faça?
## --answers--
Retrieve a subset of rows and columns by supplying integer-location arguments.
Recuperar um subconjunto de linhas e colunas fornecendo argumentos de local inteiros.
---
Access a group of rows and columns by supplying label(s) arguments.
Acessar um grupo de linhas e colunas fornecendo argumentos de etiqueta.
---
Returns the first `n` rows based on the integer argument supplied.
Retornar as primeiras `n` linhas baseadas no argumento inteiro fornecido.
## --video-solution--

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curriculum/challenges/portuguese/08-data-analysis-with-python/data-analysis-with-python-course/data-cleaning-and-visualizations.md
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---
id: 5e9a093a74c4063ca6f7c160
title: Data Cleaning and Visualizations
title: Limpar e visualizar dados
challengeType: 11
videoId: mHjxzFS5_Z0
dashedName: data-cleaning-and-visualizations
@ -8,18 +8,18 @@ dashedName: data-cleaning-and-visualizations
# --description--
*Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.*
*Ao invés de usar notebooks.ai como foi mostrado no vídeo, você pode usar o Google Colab como substituto.*
More resources:
Mais recursos:
- [Notebooks on GitHub](https://github.com/ine-rmotr-curriculum/data-cleaning-rmotr-freecodecamp)
- [How to open Notebooks from GitHub using Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
- [Notebooks no GitHub](https://github.com/ine-rmotr-curriculum/data-cleaning-rmotr-freecodecamp)
- [Como abrir notebooks do GitHub usando o Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
# --question--
## --text--
When using Matplotlib's global API, what does the order of numbers mean here?
Ao usar a API global do matplotlib, o que significa a ordem dos números aqui?
```py
plt.subplot(1, 2, 1)
@ -27,15 +27,15 @@ plt.subplot(1, 2, 1)
## --answers--
My figure will have one column, two rows, and I am going to start drawing in the first (left) plot.
Minha figura terá uma coluna e duas linhas. Eu vou começar a desenhar no primeiro gráfico (à esquerda).
---
I am going to start drawing in the first (left) plot, my figure will have two rows, and my figure will have one column.
Vou começar a desenhar no primeiro gráfico (à esquerda). A minha figura terá duas linhas e a minha figura terá uma coluna.
---
My figure will have one row, two columns, and I am going to start drawing in the first (left) plot.
Minha figura terá uma linha e duas colunas. Eu vou começar a desenhar no primeiro gráfico (à esquerda).
## --video-solution--

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curriculum/challenges/portuguese/08-data-analysis-with-python/data-analysis-with-python-course/data-cleaning-duplicates.md
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---
id: 5e9a093a74c4063ca6f7c15f
title: Data Cleaning Duplicates
title: Limpar dados duplicados
challengeType: 11
videoId: kj7QqjXhH6A
dashedName: data-cleaning-duplicates
@ -8,30 +8,30 @@ dashedName: data-cleaning-duplicates
# --description--
*Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.*
*Ao invés de usar notebooks.ai como foi mostrado no vídeo, você pode usar o Google Colab como substituto.*
More resources:
Mais recursos:
- [Notebooks on GitHub](https://github.com/ine-rmotr-curriculum/data-cleaning-rmotr-freecodecamp)
- [How to open Notebooks from GitHub using Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
- [Notebooks no GitHub](https://github.com/ine-rmotr-curriculum/data-cleaning-rmotr-freecodecamp)
- [Como abrir notebooks do GitHub usando o Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
# --question--
## --text--
The Python method `.duplicated()` returns a boolean Series for your DataFrame. `True` is the return value for rows that:
O método `.duplicated()` do Python retorna uma série booleana para o seu DataFrame. `True` é o valor de retorno para as linhas que:
## --answers--
contain a duplicate, where the value for the row contains the first occurrence of that value.
contém uma duplicata, onde o valor para a linha contém a primeira ocorrência desse valor.
---
contain a duplicate, where the value for the row is at least the second occurrence of that value.
contém uma duplicata, onde o valor para a linha é, ao menos, a segunda ocorrência desse valor.
---
contain a duplicate, where the value for the row contains either the first or second occurrence.
contém uma duplicata, onde o valor para a linha contém a primeira ou a segunda ocorrência.
## --video-solution--

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curriculum/challenges/portuguese/08-data-analysis-with-python/data-analysis-with-python-course/data-cleaning-introduction.md
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@ -1,6 +1,6 @@
---
id: 5e9a093a74c4063ca6f7c15d
title: Data Cleaning Introduction
title: Introduzir a limpeza de dados
challengeType: 11
videoId: ovYNhnltVxY
dashedName: data-cleaning-introduction
@ -8,18 +8,18 @@ dashedName: data-cleaning-introduction
# --description--
*Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.*
*Ao invés de usar notebooks.ai como foi mostrado no vídeo, você pode usar o Google Colab como substituto.*
More resources:
Mais recursos:
- [Notebooks on GitHub](https://github.com/ine-rmotr-curriculum/data-cleaning-rmotr-freecodecamp)
- [How to open Notebooks from GitHub using Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
- [Notebooks no GitHub](https://github.com/ine-rmotr-curriculum/data-cleaning-rmotr-freecodecamp)
- [Como abrir notebooks do GitHub usando o Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
# --question--
## --text--
What will the following code print out?
O que será impresso pelo código a seguir?
```py
import pandas as pd

16
curriculum/challenges/portuguese/08-data-analysis-with-python/data-analysis-with-python-course/how-to-use-jupyter-notebooks-intro.md
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---
id: 5e9a093a74c4063ca6f7c14f
title: How to use Jupyter Notebooks Intro
title: Como usar a introdução aos Jupyter Notebooks
challengeType: 11
videoId: h8caJq2Bb9w
dashedName: how-to-use-jupyter-notebooks-intro
@ -8,18 +8,18 @@ dashedName: how-to-use-jupyter-notebooks-intro
# --description--
*Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.*
*Ao invés de usar notebooks.ai como foi mostrado no vídeo, você pode usar o Google Colab como substituto.*
More resources:
Mais recursos:
- [Notebooks on GitHub](https://github.com/ine-rmotr-curriculum/ds-content-interactive-jupyterlab-tutorial)
- [How to open Notebooks from GitHub using Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
- [Notebooks no GitHub](https://github.com/ine-rmotr-curriculum/ds-content-interactive-jupyterlab-tutorial)
- [Como abrir notebooks do GitHub usando o Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
# --question--
## --text--
What is **not** allowed in a Jupyter Notebook's cell?
O que **não** é permitido na célula de um Jupyter Notebook?
## --answers--
@ -27,11 +27,11 @@ Markdown
---
Python code
Código do Python
---
An Excel sheet
Uma planilha do Excel
## --video-solution--

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curriculum/challenges/portuguese/08-data-analysis-with-python/data-analysis-with-python-course/jupyter-notebooks-cells.md
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@ -1,6 +1,6 @@
---
id: 5e9a093a74c4063ca6f7c150
title: Jupyter Notebooks Cells
title: Conhecer as células do Jupyter Notebooks
challengeType: 11
videoId: 5PPegAs9aLA
dashedName: jupyter-notebooks-cells
@ -8,30 +8,30 @@ dashedName: jupyter-notebooks-cells
# --description--
*Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.*
*Ao invés de usar notebooks.ai como foi mostrado no vídeo, você pode usar o Google Colab como substituto.*
More resources:
Mais recursos:
- [Notebooks on GitHub](https://github.com/ine-rmotr-curriculum/ds-content-interactive-jupyterlab-tutorial)
- [How to open Notebooks from GitHub using Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
- [Notebooks no GitHub](https://github.com/ine-rmotr-curriculum/ds-content-interactive-jupyterlab-tutorial)
- [Como abrir notebooks do GitHub usando o Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
# --question--
## --text--
What are the three main types of Jupyter Notebook Cell?
Quais são os três principais tipos de célula dos Jupyter Notebooks?
## --answers--
Code, Markdown, and Python
Código, markdown e Python
---
Code, Markdown, and Raw
Código, markdown e bruto
---
Markdown, Python, and Raw
Markdown, Python e bruto
## --video-solution--

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curriculum/challenges/portuguese/08-data-analysis-with-python/data-analysis-with-python-course/jupyter-notebooks-importing-and-exporting-data.md
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---
id: 5e9a093a74c4063ca6f7c151
title: Jupyter Notebooks Importing and Exporting Data
title: Importar e exportar os dados dos Jupyter Notebooks
challengeType: 11
videoId: k1msxD3JIxE
dashedName: jupyter-notebooks-importing-and-exporting-data
@ -8,38 +8,38 @@ dashedName: jupyter-notebooks-importing-and-exporting-data
# --description--
*Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.*
*Ao invés de usar notebooks.ai como foi mostrado no vídeo, você pode usar o Google Colab como substituto.*
More resources:
Mais recursos:
- [Notebooks on GitHub](https://github.com/ine-rmotr-curriculum/ds-content-interactive-jupyterlab-tutorial)
- [How to open Notebooks from GitHub using Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
- [Notebooks no GitHub](https://github.com/ine-rmotr-curriculum/ds-content-interactive-jupyterlab-tutorial)
- [Como abrir notebooks do GitHub usando o Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
# --question--
## --text--
What kind of data can you import and work with in a Jupyter Notebook?
Que tipo de dados você pode importar e trabalhar em um Jupyter Notebook?
## --answers--
Excel files.
Arquivos do Excel.
---
CSV files.
Arquivos CSV.
---
XML files.
Arquivos XML.
---
Data from an API.
Dados de uma API.
---
All of the above.
Todas as anteriores.
## --video-solution--

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curriculum/challenges/portuguese/08-data-analysis-with-python/data-analysis-with-python-course/numpy-operations.md
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@ -1,6 +1,6 @@
---
id: 5e9a093a74c4063ca6f7c155
title: Numpy Operations
title: Conhecer operações do NumPy
challengeType: 11
videoId: eqSVcJbaPdk
dashedName: numpy-operations
@ -8,18 +8,18 @@ dashedName: numpy-operations
# --description--
*Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.*
*Ao invés de usar notebooks.ai como foi mostrado no vídeo, você pode usar o Google Colab como substituto.*
More resources:
Mais recursos:
- [Notebooks on GitHub](https://github.com/ine-rmotr-curriculum/freecodecamp-intro-to-numpy)
- [How to open Notebooks from GitHub using Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
- [Notebooks no GitHub](https://github.com/ine-rmotr-curriculum/freecodecamp-intro-to-numpy)
- [Como abrir notebooks do GitHub usando o Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
# --question--
## --text--
What is the value of `a` after you run the following code?
Qual é o valor de `a` depois de executar o seguinte código?
```py
a = np.arange(5)

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curriculum/challenges/portuguese/08-data-analysis-with-python/data-analysis-with-python-course/pandas-introduction.md
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@ -1,6 +1,6 @@
---
id: 5e9a093a74c4063ca6f7c158
title: Pandas Introduction
title: Introduzir o Pandas
challengeType: 11
videoId: 0xACW-8cZU0
dashedName: pandas-introduction
@ -8,18 +8,18 @@ dashedName: pandas-introduction
# --description--
*Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.*
*Ao invés de usar notebooks.ai como foi mostrado no vídeo, você pode usar o Google Colab como substituto.*
More resources:
Mais recursos:
- [Notebooks on GitHub](https://github.com/ine-rmotr-curriculum/freecodecamp-intro-to-pandas)
- [How to open Notebooks from GitHub using Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
- [Notebooks no GitHub](https://github.com/ine-rmotr-curriculum/freecodecamp-intro-to-pandas)
- [Como abrir notebooks do GitHub usando o Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
# --question--
## --text--
What will the following code print out?
O que será impresso pelo código a seguir?
```py
import pandas as pd

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curriculum/challenges/portuguese/08-data-analysis-with-python/data-analysis-with-python-course/parsing-html-and-saving-data.md
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@ -1,6 +1,6 @@
---
id: 5e9a093a74c4063ca6f7c164
title: Parsing HTML and Saving Data
title: Analisar HTML e salvar dados
challengeType: 11
videoId: bJaqnTWQmb0
dashedName: parsing-html-and-saving-data
@ -8,18 +8,18 @@ dashedName: parsing-html-and-saving-data
# --description--
*Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.*
*Ao invés de usar notebooks.ai como foi mostrado no vídeo, você pode usar o Google Colab como substituto.*
More resources:
Mais recursos:
- [Notebooks on GitHub](https://github.com/ine-rmotr-curriculum/RDP-Reading-Data-with-Python-and-Pandas/tree/master/unit-1-reading-data-with-python-and-pandas/lesson-17-reading-html-tables/files)
- [How to open Notebooks from GitHub using Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
- [Notebooks no GitHub](https://github.com/ine-rmotr-curriculum/RDP-Reading-Data-with-Python-and-Pandas/tree/master/unit-1-reading-data-with-python-and-pandas/lesson-17-reading-html-tables/files)
- [Como abrir notebooks do GitHub usando o Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
# --question--
## --text--
What Python library has the `.read_html()` method we can we use for parsing HTML documents and extracting tables?
Qual biblioteca do Python tem o método `.read_html()` que podemos usar para analisar documentos HTML e extrair tabelas?
## --answers--

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curriculum/challenges/portuguese/08-data-analysis-with-python/data-analysis-with-python-course/python-functions-and-collections.md
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@ -1,6 +1,6 @@
---
id: 5e9a093a74c4063ca6f7c166
title: Python Functions and Collections
title: Conhecer coleções e funções do Python
challengeType: 11
videoId: NzpU17ZVlUw
dashedName: python-functions-and-collections
@ -8,30 +8,30 @@ dashedName: python-functions-and-collections
# --description--
*Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.*
*Ao invés de usar notebooks.ai como foi mostrado no vídeo, você pode usar o Google Colab como substituto.*
More resources:
Mais recursos:
- [Notebooks on GitHub](https://github.com/ine-rmotr-curriculum/ds-content-python-under-10-minutes)
- [How to open Notebooks from GitHub using Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
- [Notebooks no GitHub](https://github.com/ine-rmotr-curriculum/ds-content-python-under-10-minutes)
- [Como abrir notebooks do GitHub usando o Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
# --question--
## --text--
What is the main difference between lists and tuples in Python?
Qual é a principal diferença entre listas e tuplas em Python?
## --answers--
Tuples are immutable.
Tuplas são imutáveis.
---
Lists are ordered.
Listas são ordenadas.
---
Tuples are unordered.
Tuplas são desordenadas.
## --video-solution--

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curriculum/challenges/portuguese/08-data-analysis-with-python/data-analysis-with-python-course/python-introduction.md
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@ -1,6 +1,6 @@
---
id: 5e9a093a74c4063ca6f7c165
title: Python Introduction
title: Introduzir o Python
challengeType: 11
videoId: PrQV9JkLhb4
dashedName: python-introduction
@ -8,34 +8,34 @@ dashedName: python-introduction
# --description--
*Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.*
*Ao invés de usar notebooks.ai como foi mostrado no vídeo, você pode usar o Google Colab como substituto.*
More resources:
Mais recursos:
- [Notebooks on GitHub](https://github.com/ine-rmotr-curriculum/ds-content-python-under-10-minutes)
- [How to open Notebooks from GitHub using Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
- [Notebooks no GitHub](https://github.com/ine-rmotr-curriculum/ds-content-python-under-10-minutes)
- [Como abrir notebooks do GitHub usando o Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
# --question--
## --text--
How do we define blocks of code in the body of functions in Python?
Como definimos blocos de código no corpo das funções do Python?
## --answers--
We use a set of curly braces, one on either side of each new block of our code.
Usamos um conjunto de chaves, um em cada lado de cada novo bloco de nosso código.
---
We use indentation, usually right-aligned 4 spaces.
Usamos a indentação, geralmente 4 espaços alinhados à direita.
---
We do not denote blocks of code.
Não denotamos blocos de código.
---
We could use curly braces or indentation to denote blocks of code.
Poderíamos usar chaves ou indentação para indicar blocos de código.
## --video-solution--

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curriculum/challenges/portuguese/08-data-analysis-with-python/data-analysis-with-python-course/python-iteration-and-modules.md
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@ -1,6 +1,6 @@
---
id: 5e9a093a74c4063ca6f7c167
title: Python Iteration and Modules
title: Realizar a iteração em Python e módulos
challengeType: 11
videoId: XzosGWLafrY
dashedName: python-iteration-and-modules
@ -8,18 +8,18 @@ dashedName: python-iteration-and-modules
# --description--
*Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.*
*Ao invés de usar notebooks.ai como foi mostrado no vídeo, você pode usar o Google Colab como substituto.*
More resources:
Mais recursos:
- [Notebooks on GitHub](https://github.com/ine-rmotr-curriculum/ds-content-python-under-10-minutes)
- [How to open Notebooks from GitHub using Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
- [Notebooks no GitHub](https://github.com/ine-rmotr-curriculum/ds-content-python-under-10-minutes)
- [Como abrir notebooks do GitHub usando o Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
# --question--
## --text--
How would you iterate over and print the keys and values of a dictionary named `user`?
Como você iteraria e imprimiria as chaves e valores de um dicionário chamado `user`?
## --answers--

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curriculum/challenges/portuguese/08-data-analysis-with-python/data-analysis-with-python-course/reading-data-introduction.md
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@ -1,6 +1,6 @@
---
id: 5e9a093a74c4063ca6f7c161
title: Reading Data Introduction
title: Introduzir a leitura de dados
challengeType: 11
videoId: cDnt02BcHng
dashedName: reading-data-introduction
@ -8,18 +8,18 @@ dashedName: reading-data-introduction
# --description--
*Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.*
*Ao invés de usar notebooks.ai como foi mostrado no vídeo, você pode usar o Google Colab como substituto.*
More resources:
Mais recursos:
- [Notebooks on GitHub](https://github.com/ine-rmotr-curriculum/RDP-Reading-Data-with-Python-and-Pandas/tree/master/unit-1-reading-data-with-python-and-pandas/lesson-1-reading-csv-and-txt-files/files)
- [How to open Notebooks from GitHub using Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
- [Notebooks no GitHub](https://github.com/ine-rmotr-curriculum/RDP-Reading-Data-with-Python-and-Pandas/tree/master/unit-1-reading-data-with-python-and-pandas/lesson-1-reading-csv-and-txt-files/files)
- [Como abrir notebooks do GitHub usando o Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
# --question--
## --text--
Given a file named `certificates.csv` with these contents:
Dado um arquivo chamado `certificates.csv` com este conteúdo:
<pre>
Name$Certificates$Time (in months)
@ -29,7 +29,7 @@ Ahmad$5$9
Beau$6$12
</pre>
Fill in the blanks for the missing arguments below:
Preencha as lacunas para os argumentos que faltam abaixo:
```py
import csv

12
curriculum/challenges/portuguese/08-data-analysis-with-python/data-analysis-with-python-projects/demographic-data-analyzer.md
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@ -1,6 +1,6 @@
---
id: 5e46f7e5ac417301a38fb929
title: Demographic Data Analyzer
title: Analisador de dados demográficos
challengeType: 10
forumTopicId: 462367
dashedName: demographic-data-analyzer
@ -8,17 +8,17 @@ dashedName: demographic-data-analyzer
# --description--
In this challenge you must analyze demographic data using Pandas. You are given a dataset of demographic data that was extracted from the 1994 Census database.
Neste desafio você deve analisar dados demográficos usando o Pandas. Você receberá um conjunto de dados relativos aos dados demográficos que foram extraídos do banco de dados do censo de 1994.
You can access [the full project description and starter code on Replit](https://replit.com/github/freeCodeCamp/boilerplate-demographic-data-analyzer).
Você pode acessar [a descrição completa do projeto e o código inicial no Replit](https://replit.com/github/freeCodeCamp/boilerplate-demographic-data-analyzer).
After going to that link, fork the project. Once you complete the project based on the instructions in 'README.md', submit your project link below.
Depois de ir para esse link, faça fork no projeto. Depois que você completar o projeto com base nas instruções do 'README.md', envie o link do seu projeto abaixo.
We are still developing the interactive instructional part of the data analysis with Python curriculum. For now, you will have to use other resources to learn how to pass this challenge.
Ainda estamos desenvolvendo a parte instrucional interativa do currículo de análise de dados com Python. Por enquanto, você terá que usar outros recursos para aprender a vencer este desafio.
# --hints--
It should pass all Python tests.
Ele deve passar em todos os testes do Python.
```js

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@ -1,6 +1,6 @@
---
id: 5e46f7e5ac417301a38fb928
title: Mean-Variance-Standard Deviation Calculator
title: Calculadora de média, variância e desvio padrão
challengeType: 10
forumTopicId: 462366
dashedName: mean-variance-standard-deviation-calculator
@ -8,17 +8,17 @@ dashedName: mean-variance-standard-deviation-calculator
# --description--
Create a function that uses Numpy to output the mean, variance, and standard deviation of the rows, columns, and elements in a 3 x 3 matrix.
Crie uma função que use o NumPy para retornar a média, variação e o desvio-padrão das linhas, colunas e elementos em uma matriz de 3 x 3.
You can access [the full project description and starter code on Replit](https://replit.com/github/freeCodeCamp/boilerplate-mean-variance-standard-deviation-calculator).
Você pode acessar [a descrição completa do projeto e o código inicial no Replit](https://replit.com/github/freeCodeCamp/boilerplate-mean-variance-standard-deviation-calculator).
After going to that link, fork the project. Once you complete the project based on the instructions in 'README.md', submit your project link below.
Depois de ir para esse link, faça fork no projeto. Depois que você completar o projeto com base nas instruções do 'README.md', envie o link do seu projeto abaixo.
We are still developing the interactive instructional part of the data analysis with Python curriculum. For now, you will have to use other resources to learn how to pass this challenge.
Ainda estamos desenvolvendo a parte instrucional interativa do currículo de análise de dados com Python. Por enquanto, você terá que usar outros recursos para aprender a vencer este desafio.
# --hints--
It should pass all Python tests.
Ele deve passar em todos os testes do Python.
```js

12
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@ -1,6 +1,6 @@
---
id: 5e46f7f8ac417301a38fb92a
title: Medical Data Visualizer
title: Visualizador de dados médicos
challengeType: 10
forumTopicId: 462368
dashedName: medical-data-visualizer
@ -8,17 +8,17 @@ dashedName: medical-data-visualizer
# --description--
In this project, you will visualize and make calculations from medical examination data using matplotlib, seaborn, and pandas.
Neste projeto, você vai visualizar e fazer cálculos a partir de dados dos exames médicos usando o matplotlib, o seaborn e o pandas.
You can access [the full project description and starter code on Replit](https://replit.com/github/freeCodeCamp/boilerplate-medical-data-visualizer).
Você pode acessar [a descrição completa do projeto e o código inicial no Replit](https://replit.com/github/freeCodeCamp/boilerplate-medical-data-visualizer).
After going to that link, fork the project. Once you complete the project based on the instructions in 'README.md', submit your project link below.
Depois de ir para esse link, faça fork no projeto. Depois que você completar o projeto com base nas instruções do 'README.md', envie o link do seu projeto abaixo.
We are still developing the interactive instructional part of the data analysis with Python curriculum. For now, you will have to use other resources to learn how to pass this challenge.
Ainda estamos desenvolvendo a parte instrucional interativa do currículo de análise de dados com Python. Por enquanto, você terá que usar outros recursos para aprender a vencer este desafio.
# --hints--
It should pass all Python tests.
Ele deve passar em todos os testes do Python.
```js

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curriculum/challenges/portuguese/08-data-analysis-with-python/data-analysis-with-python-projects/sea-level-predictor.md
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@ -1,6 +1,6 @@
---
id: 5e4f5c4b570f7e3a4949899f
title: Sea Level Predictor
title: Previsor de nível do mar
challengeType: 10
forumTopicId: 462370
dashedName: sea-level-predictor
@ -8,17 +8,17 @@ dashedName: sea-level-predictor
# --description--
In this project, you will analyze a dataset of the global average sea level change since 1880. You will use the data to predict the sea level change through year 2050.
Neste projeto, você analisará um conjunto de dados da mudança média do nível do mar global desde 1880. Você utilizará os dados para prever a mudança do nível do mar até ao ano de 2050.
You can access [the full project description and starter code on Replit](https://replit.com/github/freeCodeCamp/boilerplate-sea-level-predictor).
Você pode acessar [a descrição completa do projeto e o código inicial no Replit](https://replit.com/github/freeCodeCamp/boilerplate-sea-level-predictor).
After going to that link, fork the project. Once you complete the project based on the instructions in 'README.md', submit your project link below.
Depois de ir para esse link, faça fork no projeto. Depois que você completar o projeto com base nas instruções do 'README.md', envie o link do seu projeto abaixo.
We are still developing the interactive instructional part of the data analysis with Python curriculum. For now, you will have to use other resources to learn how to pass this challenge.
Ainda estamos desenvolvendo a parte instrucional interativa do currículo de análise de dados com Python. Por enquanto, você terá que usar outros recursos para aprender a vencer este desafio.
# --hints--
It should pass all Python tests.
Ele deve passar em todos os testes do Python.
```js

4
curriculum/challenges/portuguese/08-data-analysis-with-python/numpy/accessing-and-changing-elements,-rows,-columns.md
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@ -1,6 +1,6 @@
---
id: 5e9a0a8e09c5df3cc3600ed4
title: 'Accessing and Changing Elements, Rows, Columns'
title: 'Acessar e mudar elementos, linhas, colunas'
challengeType: 11
videoId: v-7Y7koJ_N0
dashedName: accessing-and-changing-elements-rows-columns
@ -10,7 +10,7 @@ dashedName: accessing-and-changing-elements-rows-columns
## --text--
What code would change the values in the 3rd column of both of the following Numpy arrays to 20?
Qual código alteraria os valores na terceira coluna dos seguintes arrays do NumPy para 20?
```py
a = np.array([[1, 2, 3, 4, 5], [6, 7, 8, 9, 10]])

4
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@ -1,6 +1,6 @@
---
id: 5e9a0a8e09c5df3cc3600ed7
title: Copying Arrays Warning
title: Aviso de cópia de arrays
challengeType: 11
videoId: iIoQ0_L0GvA
dashedName: copying-arrays-warning
@ -10,7 +10,7 @@ dashedName: copying-arrays-warning
## --text--
What is the value of `a` after running the following code?
Qual é o valor de `a` depois de executar o seguinte código?
```py
import numpy as np

4
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@ -1,6 +1,6 @@
---
id: 5e9a0a8e09c5df3cc3600ed6
title: Initialize Array Problem
title: Inicializar problema de arrays
challengeType: 11
videoId: 0jGfH8BPfOk
dashedName: initialize-array-problem
@ -10,7 +10,7 @@ dashedName: initialize-array-problem
## --text--
What is another way to produce the following array?
Qual é a outra forma de produzir o array a seguir?
```py
[[0. 0. 0. 0. 0. 0. 0.]

4
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@ -1,6 +1,6 @@
---
id: 5e9a0a8e09c5df3cc3600ed5
title: Initializing Different Arrays
title: Inicializar arrays diferentes
challengeType: 11
videoId: CEykdsKT4U4
dashedName: initializing-different-arrays
@ -10,7 +10,7 @@ dashedName: initializing-different-arrays
## --text--
What will the following code print?
O que será impresso pelo código a seguir?
```py
a = np.array([[1, 2, 3, 4, 5], [6, 7, 8, 9, 10]])

6
curriculum/challenges/portuguese/08-data-analysis-with-python/numpy/loading-data-and-advanced-indexing.md
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@ -1,6 +1,6 @@
---
id: 5e9a0a8e09c5df3cc3600eda
title: Loading Data and Advanced Indexing
title: Carregar dados e indexação avançada
challengeType: 11
videoId: tUdBZ7pF8Jg
dashedName: loading-data-and-advanced-indexing
@ -10,14 +10,14 @@ dashedName: loading-data-and-advanced-indexing
## --text--
Given a file named `data.txt` with these contents:
Dado um arquivo chamado `data.txt` com este conteúdo:
<pre>
29,97,32,100,45
15,88,5,75,22
</pre>
What code would produce the following array?
Qual código produziria o array a seguir?
```py
[29. 32. 45. 15. 5. 22.]

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curriculum/challenges/portuguese/08-data-analysis-with-python/numpy/what-is-numpy.md
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@ -1,6 +1,6 @@
---
id: 5e9a0a8e09c5df3cc3600ed2
title: What is NumPy
title: Conhecer o NumPy
challengeType: 11
videoId: 5Nwfs5Ej85Q
dashedName: what-is-numpy
@ -10,23 +10,23 @@ dashedName: what-is-numpy
## --text--
Why are Numpy arrays faster than regular Python lists?
Por que arrays do Numpy são mais rápidos que as listas regulares do Python?
## --answers--
Numpy does not perform type checking while iterating through objects.
O NumPy não efetua a verificação de tipo durante a iteração de objetos.
---
Numpy uses fixed types.
O NumPy usa tipos fixos.
---
Numpy uses contiguous memory.
O NumPy usa memória contígua.
---
All of the above.
Todas as anteriores.
## --video-solution--