Search Results
| Search type | Search syntax |
|---|---|
| Tags | [tag] |
| Exact | "words here" |
| Author | user:1234 user:me (yours) |
| Score | score:3 (3+) score:0 (none) |
| Answers | answers:3 (3+) answers:0 (none) isaccepted:yes hasaccepted:no inquestion:1234 |
| Views | views:250 |
| Code | code:"if (foo != bar)" |
| Sections | title:apples body:"apples oranges" |
| URL | url:"*.example.com" |
| Saves | in:saves |
| Status | closed:yes duplicate:no migrated:no wiki:no |
| Types | is:question is:answer |
| Exclude | -[tag] -apples |
| For more details on advanced search visit our help page | |
Results tagged with python
Search options not deleted user 77338
Use for data science questions related to the programming language Python. Not intended for general coding questions (which should be asked on Stack Overflow).
3 votes
Accepted
Converting a Pandas Series string of multiple attributes into individual attributes?
This might Pandas convert a column of list to dummies. You can try using the MultiLabelBinarizer class from sklearn.
0 votes
Compare multiple values from a DataFrame against a single row from another
You can join df and df_st on Reference: df_merged = pd.merge(df, df_st, on="Reference", how="left") Note: The how="left" would really depend on what you want in the joined table. You can then compare …
1 vote
Accepted
How to find the mean of a column relative to another column?
You need to change inplace to False (which is the default). Setting it to True changes the dataframe in place, so you don't have to assign the column again. Also, setting inplace=True returns None. S …
2 votes
Accepted
How to display the entire output and not shortened versions
Alternatively to Marce's answer, you can display all the rows without finding N by using: with pd.option_context("display.max_rows", -1): display(train.isnull().sum())
1 vote
How do I assign specific values to categorical variables
Building on to @grov's answer, you can alternatively use map directly on the column like so: df['col1_numerical'] = df['col1'].map({ "Increased": 1, "Decreased": -1, "Neutral": 0 })