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chore(i18n,curriculum): update translations (#42918)

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curriculum/challenges/italian/08-data-analysis-with-python/data-analysis-with-python-course/introduction-to-data-analysis.md
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---
id: 5e9a093a74c4063ca6f7c14c
title: Introduction to Data Analysis
title: Introduzione all'analisi dei dati
challengeType: 11
videoId: VJrP2FUzKP0
dashedName: introduction-to-data-analysis
@ -8,31 +8,31 @@ dashedName: introduction-to-data-analysis
# --description--
More resources:
Altre risorse:
\- [Slides](https://docs.google.com/presentation/d/1cUIt8b2ySz-85_ykfeuuWsurccwTAuFPn782pZBzFsU/edit?usp=sharing)
\- [Presentazione](https://docs.google.com/presentation/d/1cUIt8b2ySz-85_ykfeuuWsurccwTAuFPn782pZBzFsU/edit?usp=sharing)
# --question--
## --text--
Which of the following is **not** part of Data Analysis?
Quale dei seguenti elementi **non** è parte dell'analisi dei dati?
## --answers--
Building statistical models and data visualizations.
Costruire modelli statistici e visualizzazioni di dati.
---
Picking a desired conclusion for the analysis.
Scegliere una conclusione desiderata per l'analisi.
---
Fixing incorrect values and removing invalid data.
Correggere i valori errati e rimuovere i dati non validi.
---
Transforming data into an appropriate data structure.
Trasformare i dati in una struttura di dati appropriata.
## --video-solution--

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curriculum/challenges/italian/08-data-analysis-with-python/data-analysis-with-python-course/numpy-algebra-and-size.md
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---
id: 5e9a093a74c4063ca6f7c157
title: Numpy Algebra and Size
title: Algebra e dimensione con Numpy
challengeType: 11
videoId: XAT97YLOKD8
dashedName: numpy-algebra-and-size
@ -8,34 +8,34 @@ dashedName: numpy-algebra-and-size
# --description--
*Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.*
*Invece di usare notebooks.ai come mostrato nel video, puoi usare Google Colab.*
More resources:
Altre risorse:
- [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)
- [Notebook su GitHub](https://github.com/ine-rmotr-curriculum/freecodecamp-intro-to-numpy)
- [Come aprire Notebooks da GitHub usando Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
# --question--
## --text--
What is the relationship between size of objects (such as lists and datatypes) in memory in Python's standard library and the NumPy library? Knowing this, what are the implications for performance?
Qual è la relazione tra le dimensioni degli oggetti (come liste e tipi di dati) nella memoria nella libreria standard di Python e nella libreria NumPy? Sapendo questo, quali sono le implicazioni per le prestazioni?
## --answers--
Standard Python objects take up much more memory to store than NumPy objects; operations on comparable standard Python and NumPy objects complete in roughly the same time.
Gli oggetti Python standard occupano molta più memoria degli oggetti NumPy; operazioni su oggetti Python e NumPy standard comparabili sono completate approssimativamente nello stesso tempo.
---
NumPy objects take up much more memory than standard Python objects; operations on NumPy objects complete very quickly compared to comparable objects in standard Python.
Gli oggetti NumPy occupano molta più memoria degli oggetti Python standard; le operazioni su oggetti NumPy sono completate molto più rapidamente rispetto agli oggetti comparabili presenti in Python standard.
---
NumPy objects take up much less memory than Standard Python objects; operations on Standard Python objects complete very quickly compared to comparable objects on NumPy Object.
Gli oggetti NumPy occupano molta meno memoria degli oggetti Python standard; le operazioni su oggetti Python standard sono completate molto più rapidamente rispetto agli oggetti comparabili su NumPy.
---
Standard Python objects take up more memory than NumPy objects; operations on NumPy objects complete very quickly compared to comparable objects in standard Python.
Gli oggetti Python standard occupano più memoria degli oggetti NumPy; le operazioni su oggetti NumPy sono completate molto più rapidamente rispetto agli oggetti comparabili presenti in Python standard.
## --video-solution--

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curriculum/challenges/italian/08-data-analysis-with-python/data-analysis-with-python-course/numpy-arrays.md
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---
id: 5e9a093a74c4063ca6f7c154
title: Numpy Arrays
title: Array di Numpy
challengeType: 11
videoId: VDYVFHBL1AM
dashedName: numpy-arrays
@ -8,18 +8,18 @@ dashedName: numpy-arrays
# --description--
*Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.*
*Invece di usare notebooks.ai come mostrato nel video, puoi usare Google Colab.*
More resources:
Altre risorse:
- [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)
- [Notebook su GitHub](https://github.com/ine-rmotr-curriculum/freecodecamp-intro-to-numpy)
- [Come aprire Notebooks da GitHub usando 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?
Cosa verrà visualizzato nella console con il seguente codice?
```py
A = np.array([

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curriculum/challenges/italian/08-data-analysis-with-python/data-analysis-with-python-course/numpy-boolean-arrays.md
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---
id: 5e9a093a74c4063ca6f7c156
title: Numpy Boolean Arrays
title: Array booleani di Numpy
challengeType: 11
videoId: N1ttsMmcVMM
dashedName: numpy-boolean-arrays
@ -8,18 +8,18 @@ dashedName: numpy-boolean-arrays
# --description--
*Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.*
*Invece di usare notebooks.ai come mostrato nel video, puoi usare Google Colab.*
More resources:
Altre risorse:
- [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)
- [Notebook su GitHub](https://github.com/ine-rmotr-curriculum/freecodecamp-intro-to-numpy)
- [Come aprire Notebooks da GitHub usando 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?
Cosa verrà visualizzato nella console con il seguente codice?
```py
a = np.arange(5)

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curriculum/challenges/italian/08-data-analysis-with-python/data-analysis-with-python-course/numpy-introduction-a.md
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---
id: 5e9a093a74c4063ca6f7c152
title: Numpy Introduction A
title: Introduzione a Numpy A
challengeType: 11
videoId: P-JjV6GBCmk
dashedName: numpy-introduction-a
@ -8,30 +8,30 @@ dashedName: numpy-introduction-a
# --description--
*Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.*
*Invece di usare notebooks.ai come mostrato nel video, puoi usare Google Colab.*
More resources:
Altre risorse:
- [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)
- [Notebook su GitHub](https://github.com/ine-rmotr-curriculum/freecodecamp-intro-to-numpy)
- [Come aprire Notebooks da GitHub usando Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
# --question--
## --text--
Why is Numpy an important, but unpopular Python library?
Perché Numpy è una libreria Python importante ma poco popolare?
## --answers--
Often you won't work directly with Numpy.
Spesso non lavorerai direttamente con Numpy.
---
It is extremely slow.
È estremamente lento.
---
Working with Numpy is difficult.
Lavorare con Numpy è difficile.
## --video-solution--

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curriculum/challenges/italian/08-data-analysis-with-python/data-analysis-with-python-course/numpy-introduction-b.md
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---
id: 5e9a093a74c4063ca6f7c153
title: Numpy Introduction B
title: Introduzione a Numpy B
challengeType: 11
videoId: YIqgrNLAZkA
dashedName: numpy-introduction-b
@ -8,34 +8,34 @@ dashedName: numpy-introduction-b
# --description--
*Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.*
*Invece di usare notebooks.ai come mostrato nel video, puoi invece usare Google Colab.*
More resources:
Altre risorse:
- [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)
- [Notebook su GitHub](https://github.com/ine-rmotr-curriculum/freecodecamp-intro-to-numpy)
- [Come aprire Notebooks da GitHub usando Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
# --question--
## --text--
About how much memory does the integer `5` consume in plain Python?
Quanta memoria consuma all'incirca in Python puro il numero intero `5`?
## --answers--
32 bits
32 bit
---
20 bytes
20 byte
---
16 bytes
16 byte
---
8 bits
8 bit
## --video-solution--

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curriculum/challenges/italian/08-data-analysis-with-python/data-analysis-with-python-course/pandas-conditional-selection-and-modifying-dataframes.md
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---
id: 5e9a093a74c4063ca6f7c15b
title: Pandas Conditional Selection and Modifying DataFrames
title: Selezione condizionale con Panda e modifica dei DataFrame
challengeType: 11
videoId: BFlH0fN5xRQ
dashedName: pandas-conditional-selection-and-modifying-dataframes
@ -8,18 +8,18 @@ dashedName: pandas-conditional-selection-and-modifying-dataframes
# --description--
*Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.*
*Invece di usare notebooks.ai come mostrato nel video, puoi usare Google Colab.*
More resources:
Altre risorse:
- [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)
- [Notebook su GitHub](https://github.com/ine-rmotr-curriculum/freecodecamp-intro-to-pandas)
- [Come aprire Notebooks da GitHub usando 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?
Cosa verrà visualizzato nella console con il seguente codice?
```py
import pandas as pd

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curriculum/challenges/italian/08-data-analysis-with-python/data-analysis-with-python-course/pandas-creating-columns.md
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@ -1,6 +1,6 @@
---
id: 5e9a093a74c4063ca6f7c15c
title: Pandas Creating Columns
title: Creazione di colonne con Panda
challengeType: 11
videoId: _sSo2XZoB3E
dashedName: pandas-creating-columns
@ -8,18 +8,18 @@ dashedName: pandas-creating-columns
# --description--
*Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.*
*Invece di usare notebooks.ai come mostrato nel video, puoi usare Google Colab.*
More resources:
Altre risorse:
- [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)
- [Notebook su GitHub](https://github.com/ine-rmotr-curriculum/freecodecamp-intro-to-pandas)
- [Come aprire Notebooks da GitHub usando Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
# --question--
## --text--
What code would add a "Certificates per month" column to the `certificates_earned` DataFrame like the one below?
Quale codice aggiungerebbe una colonna "Certificates per month" al DataFrame `certificates_earned` come mostrato sotto?
<pre> Certificates Time (in months) Certificates per month
Tom 8 16 0.50

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curriculum/challenges/italian/08-data-analysis-with-python/data-analysis-with-python-course/pandas-indexing-and-conditional-selection.md
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---
id: 5e9a093a74c4063ca6f7c159
title: Pandas Indexing and Conditional Selection
title: Indicizzazione di Pandas e selezione condizionale
challengeType: 11
videoId: '-ZOrgV_aA9A'
dashedName: pandas-indexing-and-conditional-selection
@ -8,18 +8,18 @@ dashedName: pandas-indexing-and-conditional-selection
# --description--
*Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.*
*Invece di usare notebooks.ai come mostrato nel video, puoi usare Google Colab.*
More resources:
Altre risorse:
- [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)
- [Notebook su GitHub](https://github.com/ine-rmotr-curriculum/freecodecamp-intro-to-pandas)
- [Come aprire Notebooks da GitHub usando 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?
Cosa verrà visualizzato nella console con il seguente codice?
```py
import pandas as pd

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curriculum/challenges/italian/08-data-analysis-with-python/data-analysis-with-python-course/reading-data-csv-and-txt.md
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---
id: 5e9a093a74c4063ca6f7c162
title: Reading Data CSV and TXT
title: Lettura di dati CSV e TXT
challengeType: 11
videoId: ViGEv0zOzUk
dashedName: reading-data-csv-and-txt
@ -8,18 +8,18 @@ dashedName: reading-data-csv-and-txt
# --description--
*Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.*
*Invece di usare notebooks.ai come mostrato nel video, puoi usare Google Colab.*
More resources:
Altre risorse:
- [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)
- [Notebook su 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)
- [Come aprire Notebooks da GitHub usando Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
# --question--
## --text--
How would you import the CSV file `data.csv` and store it in a DataFrame using the Pandas module?
Come faresti per importare il file CSV `data.csv` e salvarlo in un DataFrame usando il modulo Pandas?
## --answers--

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curriculum/challenges/italian/08-data-analysis-with-python/data-analysis-with-python-course/reading-data-from-databases.md
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---
id: 5e9a093a74c4063ca6f7c163
title: Reading Data from Databases
title: Leggere i dati dal database
challengeType: 11
videoId: MtgXS1MofRw
dashedName: reading-data-from-databases
@ -8,30 +8,30 @@ dashedName: reading-data-from-databases
# --description--
*Instead of using notebooks.ai like it shows in the video, you can use Google Colab instead.*
*Invece di usare notebooks.ai come mostrato nel video, puoi usare Google Colab.*
More resources:
Altre risorse:
- [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-11-reading-data-from-relational-databases/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)
- [Notebook su 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-11-reading-data-from-relational-databases/files)
- [Come aprire Notebooks da GitHub usando Google Colab.](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)
# --question--
## --text--
What method does a `Cursor` instance have and what does it allow?
Che metodo ha un'istanza di `Cursor` e che cosa permette?
## --answers--
The `Cursor` instance has a `.run()` method which allows you to run SQL queries.
L'istanza `Cursor` ha un metodo `.run()` che consente di eseguire query SQL.
---
The `Cursor` instance has a `.select()` method which allows you to select records.
L'istanza `Cursor` ha un metodo `.select()` che consente di selezionare un documento.
---
The `Cursor` instance has an `.execute()` method which will receive SQL parameters to run against the database.
L'istanza `Cursor` ha un metodo `.execute()` che riceverà i parametri SQL da eseguire sul database.
## --video-solution--