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bugfixing index
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source/classification2.md

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@@ -1123,6 +1123,7 @@ cv_10_metrics
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```
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```{index} cross-validation; folds
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```
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In this case, using 10-fold instead of 5-fold cross validation did
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reduce the standard error very slightly. In fact, due to the randomness in how the data are split, sometimes

source/intro.md

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@@ -475,7 +475,7 @@ high-level categories of languages, which include "Aboriginal languages",
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our question we want to filter our data set so we restrict our attention
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to only those languages in the "Aboriginal languages" category.
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```{index} pandas.DataFrame; [], filtering rows, logical statement, logical operator; equivalency operator, string
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```{index} pandas.DataFrame; [], filtering rows, logical statement, logical operator; equivalency (==), string
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```
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We can use the `[]` operation to obtain the subset of rows with desired values
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(ch1-adding-modifying)=
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## Adding and modifying columns
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```{index} assign, adding columns, modifying columns
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```{index} adding columns, modifying columns
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```
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Recall that our data analysis question referred to the *count* of Canadians

source/jupyter.md

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@@ -176,9 +176,6 @@ Restarting the Python session can be accomplished by clicking Restart Kernel and
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```{index} kernel, Jupyter notebook; kernel
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```
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```{index} see: Jupyter notebook; kernel
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```
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The kernel is a program that executes the code inside your notebook and
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outputs the results. Kernels for many different programming languages have
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been created for Jupyter, which means that Jupyter can interpret and execute

source/reading.md

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@@ -700,7 +700,7 @@ In `ibis`, we can do that using the `count` function from the table object.
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canlang_table.count()
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```
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```{index} execute, ibis; execute
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```{index} ibis; execute
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```
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Wait a second...this isn't the number of rows in the database. In fact, we haven't actually sent our

source/viz.md

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@@ -1021,16 +1021,16 @@ glue("can_lang_plot_legend", can_lang_plot_legend.properties(height=320, width=4
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Scatter plot of percentage of Canadians reporting a language as their mother tongue vs the primary language at home colored by language category with the legend edited.
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:::
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```{index} color palette, color blindness simulator
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```
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In {numref}`can_lang_plot_legend`, the points are colored with
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the default `altair` color scheme, which is called `"tableau10"`. This is an appropriate choice for most situations and is also easy to read for people with reduced color vision.
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In general, the color schemes that are used by default in Altair are adapted to the type of data that is displayed and selected to be easy to interpret both for people with good and reduced color vision.
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If you are unsure about a certain color combination, you can use
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this [color blindness simulator](https://www.color-blindness.com/coblis-color-blindness-simulator/) to check
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if your visualizations are color-blind friendly.
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```{index} color palette; color blindness simulator
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```
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All the available color schemes and information on how to create your own can be viewed [in the Altair documentation](https://altair-viz.github.io/user_guide/customization.html#customizing-colors).
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To change the color scheme of our chart,
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we can add the `scheme` argument in the `scale` of the `color` encoding.

source/wrangling.md

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```{index} data frame; definition
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```
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```{index} see: data frame; pandas.DataFrame
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```
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```{index} pandas.DataFrame
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```
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### Extracting rows above or below a threshold using `>` and `<`
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```{index} logical operator; greater than (>, >=), logical operator; less than (<, <=)
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```{index} logical operator; greater than (> and >=), logical operator; less than (< and <=)
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```
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```{index} see: >; logical operator
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```
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```{index} see: >=; logical operator
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```
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```{index} see: <; logical operator
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```
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```{index} see: <=; logical operator
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```
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