title_wip

**Examples:**

```
# Pivot table
result = ds.pivot_table(
    values='amount',
    index='region',
    columns='product',
    aggfunc='sum'
)

# Melt (unpivot)
result = ds.melt(
    id_vars=['name'],
    value_vars=['score1', 'score2', 'score3'],
    var_name='test',
    value_name='score'
)

# Explode arrays
result = ds.explode('tags')
```

---

## Combining / Joining[​](#combining "Direct link to Combining / Joining")

|  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Method Description|  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | `merge()` SQL-style merge|  |  |  |  |  |  |  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | `join()` Join on index|  |  |  |  |  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | `concat()` Concatenate|  |  |  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | `append()` Append rows|  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | | `combine()` Combine with function|  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | | `combine_first()` Combine with priority|  |  |  |  | | --- | --- | --- | --- | | `update()` Update values|  |  | | --- | --- | | `compare()` Show differences | | | | | | | | | | | | | | | | | |

**Examples:**

```
# Merge (join)
result = pd.merge(df1, df2, on='id', how='left')
result = df1.join(df2, on='id')

# Concatenate
result = pd.concat([df1, df2, df3])
result = pd.concat([df1, df2], axis=1)
```

---

## Binary Operations[​](#binary "Direct link to Binary Operations")

|  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Method Description|  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | `add()` / `radd()` Addition|  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | `sub()` / `rsub()` Subtraction|  |  |  |  |  |  |  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | `mul()` / `rmul()` Multiplication|  |  |  |  |  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | `div()` / `rdiv()` Division|  |  |  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | `truediv()` / `rtruediv()` True division|  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | | `floordiv()` / `rfloordiv()` Floor division|  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | | `mod()` / `rmod()` Modulo|  |  |  |  | | --- | --- | --- | --- | | `pow()` / `rpow()` Power|  |  | | --- | --- | | `dot()` Matrix multiplication | | | | | | | | | | | | | | | | | | | |

**Examples:**

```
# Arithmetic operations
result = ds['col1'].add(ds['col2'])
result = ds['price'].mul(ds['quantity'])

# With fill_value for missing data
result = ds['col1'].add(ds['col2'], fill_value=0)
```

---

## Comparison Operations[​](#comparison "Direct link to Comparison Operations")

|  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Method Description|  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | `eq()` Equal|  |  |  |  |  |  |  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | `ne()` Not equal|  |  |  |  |  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | `lt()` Less than|  |  |  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | `le()` Less than or equal|  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | | `gt()` Greater than|  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | | `ge()` Greater than or equal|  |  |  |  | | --- | --- | --- | --- | | `equals()` Test equality|  |  | | --- | --- | | `compare()` Show differences | | | | | | | | | | | | | | | | | |

---

## Function Application[​](#application "Direct link to Function Application")

|  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Method Description|  |  |  |  |  |  |  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | `apply()` Apply function|  |  |  |  |  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | `applymap()` Apply element-wise|  |  |  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | `map()` Map values|  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | | `agg()` / `aggregate()` Aggregate|  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | | `transform()` Transform|  |  |  |  | | --- | --- | --- | --- | | `pipe()` Pipe functions|  |  | | --- | --- | | `groupby()` Group by | | | | | | | | | | | | | | | |

**Examples:**

```
# Apply function
result = ds['name'].apply(lambda x: x.upper())
result = ds.apply(lambda row: row['a'] + row['b'], axis=1)

# Aggregate
result = ds.agg({'col1': 'sum', 'col2': 'mean'})
result = ds.agg(['sum', 'mean', 'std'])

# Pipe
result = (ds
    .pipe(filter_active)
    .pipe(calculate_metrics)
    .pipe(format_output)
)
```

---

## Time Series[​](#timeseries "Direct link to Time Series")