append(self, other, ignore_index: 'bool' = False, verify_integrity: 'bool' = False, sort: 'bool' = False) -> 'DataFrame'

Columns in other that are not in the caller are added as new columns.

Notes

If a list of dict/series is passed and the keys are all contained in the DataFrame's index, the order of the columns in the resulting DataFrame will be unchanged.

Iteratively appending rows to a DataFrame can be more computationally intensive than a single concatenate. A better solution is to append those rows to a list and then concatenate the list with the original DataFrame all at once.

Parameters

other : DataFrame or Series/dict-like object, or list of these

The data to append.

ignore_index : bool, default False

If True, the resulting axis will be labeled 0, 1, …, n - 1.

verify_integrity : bool, default False

If True, raise ValueError on creating index with duplicates.

sort : bool, default False

Sort columns if the columns of :None:None:`self` and other are not aligned.

versionchanged

Changed to not sort by default.

Returns

DataFrame

A new DataFrame consisting of the rows of caller and the rows of other .

Append rows of other to the end of caller, returning a new object.

See Also

concat

General function to concatenate DataFrame or Series objects.

Examples

This example is valid syntax, but we were not able to check execution

>>> df = pd.DataFrame([[1, 2], [3, 4]], columns=list('AB'), index=['x', 'y'])
... df
   A  B
x  1  2
y  3  4

This example is valid syntax, but we were not able to check execution

>>> df2 = pd.DataFrame([[5, 6], [7, 8]], columns=list('AB'), index=['x', 'y'])
... df.append(df2)
   A  B
x  1  2
y  3  4
x  5  6
y  7  8

With :None:None:`ignore_index` set to True:

This example is valid syntax, but we were not able to check execution

>>> df.append(df2, ignore_index=True)
   A  B
0  1  2
1  3  4
2  5  6
3  7  8

The following, while not recommended methods for generating DataFrames, show two ways to generate a DataFrame from multiple data sources.

Less efficient:

This example is valid syntax, but we were not able to check execution

>>> df = pd.DataFrame(columns=['A'])
... for i in range(5):
...     df = df.append({'A': i}, ignore_index=True)
... df
   A
0  0
1  1
2  2
3  3
4  4

More efficient:

This example is valid syntax, but we were not able to check execution

>>> pd.concat([pd.DataFrame([i], columns=['A']) for i in range(5)],
...           ignore_index=True)
   A
0  0
1  1
2  2
3  3
4  4

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

pandas.core.reshape.concat.concat

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them

---

File: /pandas/core/frame.py#8929
type: <class 'function'>
Commit: