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This article mainly introduces how to use the append function in pandas, has a certain reference value, interested friends can refer to, I hope you can learn a lot after reading this article, the following let Xiaobian take you to understand.

Append

Append is mainly used to append data, which is a relatively simple and direct way of data merging.

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

In the function method, the meanings of the parameters are as follows:

Other: data for append, which can be DataFrame or Series or a list of components

Ignore_index: whether to keep the original index

Verify_integrity: check whether the index is duplicated. If it is True, an error will be reported if the index is duplicated.

Sort: sort columns in union and merge mode

Next, we will demonstrate the function of this function.

Basic addition

In [41]: df1.append (df2) Out [41]: letter number0 a 11 b 20 c 31 d 4In [42]: df1.append ([df1,df2] Df3]) Out [42]: letter number animal0 a 1 NaN1 b 2 NaN0 a 1 NaN1 b 2 NaN0 c 3 NaN1 d 4 NaN0 c 3 cat1 d 4 dog

Columns reset (do not retain the original index)

In [43]: df1.append ([df1,df2,df3], ignore_index=True) Out [43]: letter number animal0 a 1 NaN1 b 2 NaN2 a 1 NaN3 b 2 NaN4 c 3 NaN5 d 4 NaN6 c 3 cat7 d 4 dog

Detect duplicates

If the index is duplicated, it fails the test and an error is reported.

In [44]: df1.append ([df1,df2], verify_integrity=True) Traceback (most recent call last):... ValueError: Indexes have overlapping values: Int64Index ([0,1], dtype='int64')

Index sort

In [46]: df1.append ([df1,df2,df3], sort=True) Out [46]: animal letter number0 NaN a 11 NaN b 20 NaN a 11 NaN b 20 NaN c 31 NaN d 40 cat c 31 dog d 4

Append Series

In [49]: s = pd.Series ({'letter':'s1','number':9}) In [50]: sOut [50]: letter s1number 9dtype: objectIn [51]: df1.append (s) Traceback (most recent call last):... TypeError: Can only append a Series if ignore_index=True or if the Series has a nameIn [53]: df1.append (s, ignore_index=True) Out [53]: letter number0 a 11 b 22 S19

Additional dictionary

This works better when crawling. Every time a piece of data is crawled, it is merged into DataFrame-like data and stored.

In [54]: dic = {'letter':'s1','number':9} In [55]: df1.append (dic, ignore_index=True) Out [55]: letter number0 a 11 b 22 s19 Thank you for reading this article carefully. I hope the article "how to use append function in pandas" shared by the editor will be helpful to you. At the same time, I hope you will support and pay attention to the industry information channel. More related knowledge is waiting for you to learn!

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