diff --git a/2-Working-With-Data/08-data-preparation/README.md b/2-Working-With-Data/08-data-preparation/README.md index 7ef4d808..127a3d20 100644 --- a/2-Working-With-Data/08-data-preparation/README.md +++ b/2-Working-With-Data/08-data-preparation/README.md @@ -265,7 +265,7 @@ Notice that when a previous value is not available for forward-filling, the null In addition to missing data, you will often encounter duplicated data in real-world datasets. Fortunately, `pandas` provides an easy means of detecting and removing duplicate entries. -- **Identifying duplicates: `duplicated`**: You can easily spot duplicate values using the `duplicated` method in pandas, which returns a Boolean mask indicating whether an entry in a `DataFrame` is a duplicate of an ealier one. Let's create another example `DataFrame` to see this in action. +- **Identifying duplicates: `duplicated`**: You can easily spot duplicate values using the `duplicated` method in pandas, which returns a Boolean mask indicating whether an entry in a `DataFrame` is a duplicate of an earlier one. Let's create another example `DataFrame` to see this in action. ```python example4 = pd.DataFrame({'letters': ['A','B'] * 2 + ['B'], 'numbers': [1, 2, 1, 3, 3]}) @@ -290,7 +290,7 @@ example4.duplicated() 4 True dtype: bool ``` -- **Dropping duplicates: `drop_duplicates`: `drop_duplicates` simply returns a copy of the data for which all of the `duplicated` values are `False`: +- **Dropping duplicates: `drop_duplicates`:** simply returns a copy of the data for which all of the `duplicated` values are `False`: ```python example4.drop_duplicates() ``` diff --git a/3-Data-Visualization/09-visualization-quantities/README.md b/3-Data-Visualization/09-visualization-quantities/README.md index c8d2c929..c07ffdf0 100644 --- a/3-Data-Visualization/09-visualization-quantities/README.md +++ b/3-Data-Visualization/09-visualization-quantities/README.md @@ -21,7 +21,7 @@ An excellent library to create both simple and sophisticated plots and charts of If you have a dataset and need to discover how much of a given item is included, one of the first tasks you have at hand will be to inspect its values. -✅ There are very good 'cheat sheets' available for Matplotlib [here](https://github.com/matplotlib/cheatsheets/blob/master/cheatsheets-1.png) and [here](https://github.com/matplotlib/cheatsheets/blob/master/cheatsheets-2.png). +✅ There are very good 'cheat sheets' available for Matplotlib [here](https://matplotlib.org/cheatsheets/cheatsheets.pdf). ## Build a line plot about bird wingspan values @@ -146,7 +146,7 @@ This bar chart, however, is unreadable because there is too much non-grouped dat Filter your data to include only the bird's category. -✅ Notice that that you use Pandas to manage the data, and then let Matplotlib do the charting. +✅ Notice that you use Pandas to manage the data, and then let Matplotlib do the charting. Since there are many categories, you can display this chart vertically and tweak its height to account for all the data: diff --git a/3-Data-Visualization/09-visualization-quantities/translations/README.es.md b/3-Data-Visualization/09-visualization-quantities/translations/README.es.md index 80167cf5..7a1aa0b0 100644 --- a/3-Data-Visualization/09-visualization-quantities/translations/README.es.md +++ b/3-Data-Visualization/09-visualization-quantities/translations/README.es.md @@ -21,7 +21,7 @@ Una excelente librería para crear gráficos tanto simples como sofisticados de Si tienes un conjunto de datos y necesitas descubrir qué cantidad de un elemento determinado está incluido, una de las primeras tareas que tienes que hacer será inspeccionar sus valores. -✅ Hay muy buenas "hojas de trucos" disponibles para Matplotlib [aquí](https://github.com/matplotlib/cheatsheets/blob/master/cheatsheets-1.png) y [aquí](https://github.com/matplotlib/cheatsheets/blob/master/cheatsheets-2.png). +✅ Hay muy buenas "hojas de trucos" disponibles para Matplotlib [aquí](https://matplotlib.org/cheatsheets/cheatsheets.pdf). ## Construir un gráfico de líneas sobre los valores de la envergadura de las aves @@ -203,4 +203,4 @@ Este conjunto de datos sobre aves ofrece una gran cantidad de información sobre Esta primera lección has recibido alguna información sobre cómo utilizar Matplotlib para visualizar cantidades. Investiga sobre otras formas de trabajar con conjuntos de datos para su visualización. [Plotly](https://github.com/plotly/plotly.py) es otra forma que no cubriremos en estas lecciones, así que echa un vistazo a lo que puede ofrecer. ## Asignación -[Líneas, dispersiones y barras](assignment.es.md) \ No newline at end of file +[Líneas, dispersiones y barras](assignment.es.md) diff --git a/3-Data-Visualization/09-visualization-quantities/translations/README.hi.md b/3-Data-Visualization/09-visualization-quantities/translations/README.hi.md index d0745bfc..77c3d1d0 100644 --- a/3-Data-Visualization/09-visualization-quantities/translations/README.hi.md +++ b/3-Data-Visualization/09-visualization-quantities/translations/README.hi.md @@ -21,7 +21,7 @@ यदि आपके पास एक डेटासेट है और यह पता लगाने की आवश्यकता है कि किसी दिए गए आइटम में से कितना शामिल है, तो आपके पास सबसे पहले कार्यों में से एक इसके मूल्यों का निरीक्षण करना होगा। -✅ माटप्लोटलिब के लिए बहुत अच्छी 'चीट शीट' उपलब्ध हैं [here](https://github.com/matplotlib/cheatsheets/blob/master/cheatsheets-1.png) and [here](https://github.com/matplotlib/cheatsheets/blob/master/cheatsheets-2.png). +✅ माटप्लोटलिब के लिए बहुत अच्छी 'चीट शीट' उपलब्ध हैं [here](https://matplotlib.org/cheatsheets/cheatsheets.pdf). ## बर्ड विंगस्पैन मूल्यों के बारे में एक लाइन प्लॉट बनाएं diff --git a/3-Data-Visualization/09-visualization-quantities/translations/README.ko.md b/3-Data-Visualization/09-visualization-quantities/translations/README.ko.md index 769d007d..8951a9d9 100644 --- a/3-Data-Visualization/09-visualization-quantities/translations/README.ko.md +++ b/3-Data-Visualization/09-visualization-quantities/translations/README.ko.md @@ -21,7 +21,7 @@ 데이터 세트가 있고 주어진 항목이 얼마나 포함되어 있는지 확인해야 하는 경우에, 가장 먼저 처리해야 하는 작업 중 하나는 해당 값을 검사하는 것입니다. -✅ Matplotlib에 사용할 수 있는 매우 좋은 '치트 시트'가 있습니다. [here](https://github.com/matplotlib/cheatsheets/blob/master/cheatsheets-1.png) and [here](https://github.com/matplotlib/cheatsheets/blob/master/cheatsheets-2.png). +✅ Matplotlib에 사용할 수 있는 매우 좋은 '치트 시트'가 있습니다. [here](https://matplotlib.org/cheatsheets/cheatsheets.pdf). ## 새 날개 길이 값에 대한 선 그래프 작성하기 diff --git a/3-Data-Visualization/09-visualization-quantities/translations/README.pt-br.md b/3-Data-Visualization/09-visualization-quantities/translations/README.pt-br.md index f0bf7bf8..03f10066 100644 --- a/3-Data-Visualization/09-visualization-quantities/translations/README.pt-br.md +++ b/3-Data-Visualization/09-visualization-quantities/translations/README.pt-br.md @@ -21,7 +21,7 @@ Uma biblioteca excelente para criar tanto gráficos simples como sofisticados e Se você tem um dataset e precisa descobrir quanto de um dado elemento está presente, uma das primeiras coisas que você precisará fazer é examinar seus valores. -✅ Existem dicas ('cheat sheets') ótimas disponíveis para o Matplotlib [aqui](https://github.com/matplotlib/cheatsheets/blob/master/cheatsheets-1.png) e [aqui](https://github.com/matplotlib/cheatsheets/blob/master/cheatsheets-2.png). +✅ Existem dicas ('cheat sheets') ótimas disponíveis para o Matplotlib [aqui](https://matplotlib.org/cheatsheets/cheatsheets.pdf). ## Construindo um gráfico de linhas sobre os valores de envergadura de aves