titanic | A set of animated icons code to insert | Icon library
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kandi X-RAY | titanic Summary
A collection of animated icons + javascript library.
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titanic Examples and Code Snippets
Community Discussions
Trending Discussions on titanic
QUESTION
I just noticed that read_csv()
somehow uses random numbers which is unexpected (at least to me). The corresponding base R function read.csv()
does not do that. So, what does read_csv()
use the random numbers for? I looked into the documentation but could not find a clear answer to that. Are the random numbers related to the guess_max
argument?
ANSWER
Answered 2021-Jun-10 at 19:21tl;dr somewhere deep in the guts of the cli
package (called to generate the pretty-printed output about column types), the code is generating a random string to use as a label.
A major clue is that
QUESTION
I am new to python . i am trying to run the below code but the results are not as expected:
...ANSWER
Answered 2021-Jun-06 at 21:17There is no need for the nested loop.
QUESTION
I'm trying to use pandas profiling
on titanic dateset.
Under the overview section there are some features with caption "HIGH CORRELATION
"
- I know what is the meaning of correlation, but the caption doesn't tell which feature is correlated to this feature ?
- So what is the meaning of "
HIGH CORRELATION
" in the pandas profiling doc ?
ANSWER
Answered 2021-Jun-06 at 04:25QUESTION
I'm working with PyTorch tutorial, slightly modified to use Titanic dataset. I'm using very simple network of Linear(Dense) with ReLU... I'd like to predict survival status based on age, fare and sex for example.
I experienced a strange behavior with a simple neural network (I'm experimenting on Google Colab). Sometimes when I execute training, the accuracy doesn't change at all. It's strange because I'm recreating the model...
...ANSWER
Answered 2021-Jun-04 at 17:03As this is a classification problem, your neural network's last layer should not have a relu
activation function.
Code Snippet:
QUESTION
Python beginner here...
Trying to understand how to use OneHotEncoder from the sklearn.preprocessing library. I feel pretty confident in using it in combination with fit_transform so that the results can also be fit to the test dataframe. Where I get confused is what to do with the resulting encoded array. Do you then convert the ohe results back to a dataframe and append it to the existing train/test dataframe?
The ohe method seems a lot more cumbersome than the pd.get_dummies method, but from my understanding using ohe with fit_transform makes it easier to apply the same transformation to the test data.
Searched for hours and having a lot of trouble trying to find a good answer for this.
Example with the widely used Titanic dataset:
...ANSWER
Answered 2021-Jun-02 at 02:56Your intuition is correct: pandas.get_dummies()
is a lot easier to use, but the advantage of using OHE is that it will always apply the same transformation to unseen data. You can also export the instance using pickle
or joblib
and load it in other scripts.
There may be a way to directly reattach the encoded columns back to the original pandas.DataFrame
. Personally, I go about it the long way. That is, I fit the encoder, transform the data, attach the output back to the DataFrame and drop the original column.
QUESTION
movies = [
("Titanic", 20000000),
("Dracula", 9000000),
("James Bond", 4500000),
("Pirates of the Caribbean: On Stranger Tides", 379000000),
("Avengers: Age of Ultron", 365000000),
("Avengers: Endgame", 356000000),
("Incredibles 2", 200000000)
]
...ANSWER
Answered 2021-May-24 at 15:09The normal approach for calculating averages would work here. Something along the lines of
QUESTION
I'm working on a popular Titanic dataset on Kaggle, and I would like to create a bar chart showing the numbers of survivors vs. deceased by gender. On the x-axis, I want gender (male/female). I want to have the survivors and deceased stacked and color coded.
Here is my current code, which produces four bars for each combination of male/survived, male/deceased, female/survived, female/deceased:
...ANSWER
Answered 2021-May-16 at 16:29With some example data I believe this is what you are looking for, using matplotlib
:
QUESTION
I am trying to get visualizations from titanic dataset:
...ANSWER
Answered 2021-May-16 at 18:55You forgot to specify the axis for each plot, so it is plotting them all on the same axis.
QUESTION
I've figured out how to run a 2-way anova on several variables in my data frame, but not sure how to get this into a format that could be easily exported to a csv file or excel. Ideally, I'd like it to have this in a format where each of my several hundred dependent variables is in it's own row, with the pVaules and Fvalues
I've made an example using the titanic dataset. In this case I've set Sex & Embarked as my categorical variables, and would like the output for the effects of Sex
Embarked
and ~Interaction
somehow saved to a file. I'm open to suggestions on how to output this -- just want to be able to easily identify what values are significant, ideally with each dependent variable on its own line.
ANSWER
Answered 2021-Apr-09 at 04:34You can extract the relevant statistics from the summary
or store the model in a list and use broom::tidy
on it to get all the stats together in a dataframe. Use map
functions to run it on list of models.
QUESTION
i am just doing titanic dataset machine learning problem.I seperate numerical and categorical value in my dataset.and want to plot histogram all numerical values but i doesnt show.Can anyone help me to fix this?My code:
...ANSWER
Answered 2021-May-11 at 09:39It seems that you just need to reset the plot with plt.figure() in each iteration:
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