Update code listings

This commit is contained in:
Michael Hartl
2023-02-04 20:13:05 -08:00
parent 51494ca0ce
commit e9030432e6
7 changed files with 43 additions and 34 deletions
+9 -15
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@@ -1,15 +1,9 @@
>>> titanic["Age"].notna()
Name
Braund, Mr. Owen Harris True
Cumings, Mrs. John Bradley (Florence Briggs Thayer) True
Heikkinen, Miss. Laina True
Futrelle, Mrs. Jacques Heath (Lily May Peel) True
Allen, Mr. William Henry True
...
Montvila, Rev. Juozas True
Graham, Miss. Margaret Edith True
Johnston, Miss. Catherine Helen "Carrie" False
Behr, Mr. Karl Howell True
Dooley, Mr. Patrick True
Name: Age, Length: 891, dtype: bool
>>> valid_ages = titanic[titanic["Age"].notna()]
>>> titanic = pd.read_csv(URL, index_col="Name")
>>> titanic.head()
PassengerId ... Embarked
Name ...
Braund, Mr. Owen Harris 1 ... S
Cumings, Mrs. John Bradley (Florence Briggs Tha... 2 ... C
Heikkinen, Miss. Laina 3 ... S
Futrelle, Mrs. Jacques Heath (Lily May Peel) 4 ... S
Allen, Mr. William Henry 5 ... S
+15 -2
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@@ -1,2 +1,15 @@
titanic[(titanic["Sex"] == "female") &
(titanic["Pclass"] == 3)]["Survived"].mean()
>>> titanic["Age"].notna()
Name
Braund, Mr. Owen Harris True
Cumings, Mrs. John Bradley (Florence Briggs Thayer) True
Heikkinen, Miss. Laina True
Futrelle, Mrs. Jacques Heath (Lily May Peel) True
Allen, Mr. William Henry True
...
Montvila, Rev. Juozas True
Graham, Miss. Margaret Edith True
Johnston, Miss. Catherine Helen "Carrie" False
Behr, Mr. Karl Howell True
Dooley, Mr. Patrick True
Name: Age, Length: 891, dtype: bool
>>> valid_ages = titanic[titanic["Age"].notna()]
+2 -4
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@@ -1,4 +1,2 @@
male_passengers = titanic[titanic["Sex"] == "male"]
female_passengers = titanic[titanic["Sex"] == "female"]
valid_male_ages = male_passengers[titanic["Age"].notna()]
valid_female_ages = female_passengers[titanic["Age"].notna()]
titanic[(titanic["Sex"] == "female") &
(titanic["Pclass"] == 3)]["Survived"].mean()
+4 -1
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@@ -1 +1,4 @@
>>> from sklearn.linear_model import LinearRegression
male_passengers = titanic[titanic["Sex"] == "male"]
female_passengers = titanic[titanic["Sex"] == "female"]
valid_male_ages = male_passengers[titanic["Age"].notna()]
valid_female_ages = female_passengers[titanic["Age"].notna()]
+1 -5
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@@ -1,5 +1 @@
from sklearn.linear_model import LogisticRegression
from sklearn.naive_bayes import GaussianNB
from sklearn.linear_model import Perceptron
from sklearn.tree import DecisionTreeClassifier
from sklearn.ensemble import RandomForestClassifier
>>> from sklearn.linear_model import LinearRegression
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@@ -1,7 +1,5 @@
Model
Score
0.854749 Decision Tree
0.854749 Random Forest
0.787709 Logistic Regression
0.770950 Naive Bayes
0.743017 Perceptron
from sklearn.linear_model import LogisticRegression
from sklearn.naive_bayes import GaussianNB
from sklearn.linear_model import Perceptron
from sklearn.tree import DecisionTreeClassifier
from sklearn.ensemble import RandomForestClassifier
+7
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@@ -0,0 +1,7 @@
Model
Score
0.854749 Decision Tree
0.854749 Random Forest
0.787709 Logistic Regression
0.770950 Naive Bayes
0.743017 Perceptron