General Functions¶
General functions are the most commonly used functions in Pandas. They include functions for data manipulation, data cleaning, data merging, and more.
Data Manipulations¶
| Function | Description |
|---|---|
| pd.concat | Concatenate pandas objects along a particular axis with optional set logic along the other axes. |
| pd.crosstab | Compute a simple cross-tabulation of two (or more) factors. |
| pd.cut | Bin values into discrete intervals. |
| pd.qcut | Quantile-based discretization function. |
| pd.get_dummies | Convert categorical variable into dummy/indicator variables. |
| pd.merge | Merge DataFrame or named Series objects with a database-style join. |
| pd.pivot | Reshape data (produce a “pivot” table) based on column values. |
| pd.pivot_table | Create a spreadsheet-style pivot table as a DataFrame. |
| pd.unique | Hash table-based unique. |
Top Level Missing Data¶
| Function | Description |
|---|---|
| pd.isna | Detect missing values. |
| pd.notna | Detect existing (non-missing) values. |
| pd.isnull | Detect missing values. |
| pd.notnull | Detect existing (non-missing) values. |
Top Level Conversions¶
| Function | Description |
|---|---|
| pd.to_numeric | Convert argument to a numeric type. |