From 60526b022f0d2d098693448d361972613f20ed4d Mon Sep 17 00:00:00 2001 From: Jen Looper Date: Mon, 19 Jul 2021 10:20:02 -0400 Subject: [PATCH] changing classification file name to cleaned_cuisines --- 4-Classification/1-Introduction/README.md | 2 +- 4-Classification/1-Introduction/solution/notebook.ipynb | 2 +- 4-Classification/1-Introduction/translations/README.tr.md | 2 +- 4-Classification/1-Introduction/translations/README.zh-cn.md | 2 +- 4-Classification/2-Classifiers-1/README.md | 2 +- 4-Classification/2-Classifiers-1/solution/notebook.ipynb | 2 +- 4-Classification/3-Classifiers-2/README.md | 2 +- 4-Classification/3-Classifiers-2/notebook.ipynb | 2 +- 4-Classification/3-Classifiers-2/solution/notebook.ipynb | 2 +- 4-Classification/4-Applied/README.md | 2 +- 4-Classification/4-Applied/solution/notebook.ipynb | 2 +- .../data/{cleaned_cuisine.csv => cleaned_cuisines.csv} | 0 12 files changed, 11 insertions(+), 11 deletions(-) rename 4-Classification/data/{cleaned_cuisine.csv => cleaned_cuisines.csv} (100%) diff --git a/4-Classification/1-Introduction/README.md b/4-Classification/1-Introduction/README.md index 4490131c..8e075f0e 100644 --- a/4-Classification/1-Introduction/README.md +++ b/4-Classification/1-Introduction/README.md @@ -275,7 +275,7 @@ Now that you have cleaned the data, use [SMOTE](https://imbalanced-learn.org/dev ```python transformed_df.head() transformed_df.info() - transformed_df.to_csv("../data/cleaned_cuisine.csv") + transformed_df.to_csv("../data/cleaned_cuisines.csv") ``` This fresh CSV can now be found in the root data folder. diff --git a/4-Classification/1-Introduction/solution/notebook.ipynb b/4-Classification/1-Introduction/solution/notebook.ipynb index c5b8c629..5abb9693 100644 --- a/4-Classification/1-Introduction/solution/notebook.ipynb +++ b/4-Classification/1-Introduction/solution/notebook.ipynb @@ -622,7 +622,7 @@ "metadata": {}, "outputs": [], "source": [ - "transformed_df.to_csv(\"../../data/cleaned_cuisine.csv\")" + "transformed_df.to_csv(\"../../data/cleaned_cuisines.csv\")" ] }, { diff --git a/4-Classification/1-Introduction/translations/README.tr.md b/4-Classification/1-Introduction/translations/README.tr.md index e4cc372a..fd0e2184 100644 --- a/4-Classification/1-Introduction/translations/README.tr.md +++ b/4-Classification/1-Introduction/translations/README.tr.md @@ -275,7 +275,7 @@ Veriyi temizlediniz, şimdi [SMOTE](https://imbalanced-learn.org/dev/references/ ```python transformed_df.head() transformed_df.info() - transformed_df.to_csv("../../data/cleaned_cuisine.csv") + transformed_df.to_csv("../../data/cleaned_cuisines.csv") ``` Bu yeni CSV şimdi kök data (veri) klasöründe görülebilir. diff --git a/4-Classification/1-Introduction/translations/README.zh-cn.md b/4-Classification/1-Introduction/translations/README.zh-cn.md index 2e258f3f..adef7c8a 100644 --- a/4-Classification/1-Introduction/translations/README.zh-cn.md +++ b/4-Classification/1-Introduction/translations/README.zh-cn.md @@ -269,7 +269,7 @@ Scikit-learn项目提供多种对数据进行分类的算法，你需要根据 ```python transformed_df.head() transformed_df.info() - transformed_df.to_csv("../data/cleaned_cuisine.csv") + transformed_df.to_csv("../data/cleaned_cuisines.csv") ``` 这个全新的CSV文件可以在数据根目录中被找到。 diff --git a/4-Classification/2-Classifiers-1/README.md b/4-Classification/2-Classifiers-1/README.md index 0db1aeba..c5588f1b 100644 --- a/4-Classification/2-Classifiers-1/README.md +++ b/4-Classification/2-Classifiers-1/README.md @@ -15,7 +15,7 @@ Assuming you completed [Lesson 1](../1-Introduction/README.md), make sure that a ```python import pandas as pd - cuisines_df = pd.read_csv("../../data/cleaned_cuisine.csv") + cuisines_df = pd.read_csv("../../data/cleaned_cuisines.csv") cuisines_df.head() ``` diff --git a/4-Classification/2-Classifiers-1/solution/notebook.ipynb b/4-Classification/2-Classifiers-1/solution/notebook.ipynb index a819dbe5..770ac85c 100644 --- a/4-Classification/2-Classifiers-1/solution/notebook.ipynb +++ b/4-Classification/2-Classifiers-1/solution/notebook.ipynb @@ -47,7 +47,7 @@ ], "source": [ "import pandas as pd\n", - "cuisines_df = pd.read_csv(\"../../data/cleaned_cuisine.csv\")\n", + "cuisines_df = pd.read_csv(\"../../data/cleaned_cuisines.csv\")\n", "cuisines_df.head()" ] }, diff --git a/4-Classification/3-Classifiers-2/README.md b/4-Classification/3-Classifiers-2/README.md index dd25926e..9720c763 100644 --- a/4-Classification/3-Classifiers-2/README.md +++ b/4-Classification/3-Classifiers-2/README.md @@ -6,7 +6,7 @@ In this second classification lesson, you will explore more ways to classify num ### Prerequisite -We assume that you have completed the previous lessons and have a cleaned dataset in your `data` folder called _cleaned_cuisine.csv_ in the root of this 4-lesson folder. +We assume that you have completed the previous lessons and have a cleaned dataset in your `data` folder called _cleaned_cuisines.csv_ in the root of this 4-lesson folder. ### Preparation diff --git a/4-Classification/3-Classifiers-2/notebook.ipynb b/4-Classification/3-Classifiers-2/notebook.ipynb index f4dec474..4659a7b6 100644 --- a/4-Classification/3-Classifiers-2/notebook.ipynb +++ b/4-Classification/3-Classifiers-2/notebook.ipynb @@ -47,7 +47,7 @@ ], "source": [ "import pandas as pd\n", - "cuisines_df = pd.read_csv(\"../data/cleaned_cuisine.csv\")\n", + "cuisines_df = pd.read_csv(\"../data/cleaned_cuisines.csv\")\n", "cuisines_df.head()" ] }, diff --git a/4-Classification/3-Classifiers-2/solution/notebook.ipynb b/4-Classification/3-Classifiers-2/solution/notebook.ipynb index d953c603..a089b21f 100644 --- a/4-Classification/3-Classifiers-2/solution/notebook.ipynb +++ b/4-Classification/3-Classifiers-2/solution/notebook.ipynb @@ -47,7 +47,7 @@ ], "source": [ "import pandas as pd\n", - "cuisines_df = pd.read_csv(\"../../data/cleaned_cuisine.csv\")\n", + "cuisines_df = pd.read_csv(\"../../data/cleaned_cuisines.csv\")\n", "cuisines_df.head()" ] }, diff --git a/4-Classification/4-Applied/README.md b/4-Classification/4-Applied/README.md index 773271a1..1f3573c2 100644 --- a/4-Classification/4-Applied/README.md +++ b/4-Classification/4-Applied/README.md @@ -40,7 +40,7 @@ First, train a classification model using the cleaned cuisines dataset we used. 1. Then, work with your data in the same way you did in previous lessons, by reading a CSV file using `read_csv()`: ```python - data = pd.read_csv('../data/cleaned_cuisine.csv') + data = pd.read_csv('../data/cleaned_cuisines.csv') data.head() ``` diff --git a/4-Classification/4-Applied/solution/notebook.ipynb b/4-Classification/4-Applied/solution/notebook.ipynb index 5ed9da52..b388d2ca 100644 --- a/4-Classification/4-Applied/solution/notebook.ipynb +++ b/4-Classification/4-Applied/solution/notebook.ipynb @@ -115,7 +115,7 @@ } ], "source": [ - "data = pd.read_csv('../../data/cleaned_cuisine.csv')\n", + "data = pd.read_csv('../../data/cleaned_cuisines.csv')\n", "data.head()" ] }, diff --git a/4-Classification/data/cleaned_cuisine.csv b/4-Classification/data/cleaned_cuisines.csv similarity index 100% rename from 4-Classification/data/cleaned_cuisine.csv rename to 4-Classification/data/cleaned_cuisines.csv