[Term Entry] Python:Pandas built-in-functions: .concat()

content/pandas/concepts/built-in-functions/terms/concat/concat.md

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+---
+Title: '.concat()'
+Description: 'Concatenates multiple dataframes or series along a particular axis.'
+Subjects:
+  - 'Computer Science'
+  - 'Data Science'
+Tags:
+  - 'Data Structures'
+  - 'Functions'
+  - 'Pandas'
+CatalogContent:
+  - 'learn-python-3'
+  - 'paths/computer-science'
+---
+
+The **`.concat()`** function is used to concatenate and combine multiple [`DataFrames`](https://www.codecademy.com/resources/docs/pandas/dataframe) or `Series` along a particular axis.
+
+## Syntax
+
+```pseudo
+pandas.concat(objs, axis=0, join='outer', ignore_index=False, keys=None, levels=None, names=None, verify_integrity=False, sort=False, copy=True)
+```
+
+- `objs`: Denotes the objects to concatenate, which can be a sequence or mapping of pandas `Series` or `DataFrame` objects. It must be specified and can be passed as a list, tuple, dictionary, Series, or DataFrame.
+- `axis`: Specifies the axis to concatenate the objects. The default value is 0 for rows, while 1 represents columns.
+- `join`: Determines how to handle indexes on other axes. Options include "outer" (default), "inner," "left," or "right."
+- `ignore_index`: If `True`, reset the index in the resulting DataFrame. The new axis will be labeled 0, ..., n-1. The default value is `False`.
+- `keys`: Constructs a hierarchical index using the provided keys as the outermost level. The default value is `None`.
+- `levels`: Specific levels to use for constructing a MultiIndex if keys are provided. The default value is `None`.
+- `names`: Names for the levels generated in the hierarchical index. The default value is `None`.
+- `verify_integrity`: If `True`, checks whether the new concatenated axis contains duplicates. The default value is `False`.
+- `sort`: If `True`, sorts the resulting `Series` or `Dataframe` by the keys. The default value is `False`.
+- `copy`: If `False`, avoid copying data unnecessarily. The default value is `True`.
+
+> **Note:** Only the `objs` parameter is required; all other parameters are optional.
+
+## Example
+
+The example below demonstrates the use of `.concat()` method:
+
+```py
+import pandas as pd
+
+df1 = pd.DataFrame({'A': [1, 2], 'B': [3, 4]})
+df2 = pd.DataFrame({'A': [5, 6], 'B': [7, 8]})
+
+result = pd.concat([df1, df2])
+print(result)
+```
+
+The example will result in a new `DataFrame` created by concatenating `df1` and `df2` along the rows. The output is as follows:
+
+```shell
+   A   B
+0  1   3
+1  2   4
+0  5   7
+1  6   8
+```
+
+## Codebyte Example
+
+The code demonstrates the `.concat()` function on two DataFrames, concatenating `df1` and `df2` column-wise (`axis=1`) and using `keys` to create a hierarchical column index:
+
+```codebyte/python
+import pandas as pd
+
+df1 = pd.DataFrame({'A' : [1,2,3,4,5], 'B' : [6,7,8,9,10]})
+df2 = pd.DataFrame({'C' : [11,12,13,14,15], 'D' : [16,17,18,19,20]})
+
+result = pd.concat([df1, df2], axis=1, keys = ['df1', 'df2'])
+
+print(result)
+```