append dataframe pandas

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showing results for - "append dataframe pandas"
Nolhan
22 Jul 2020
1df = df.append({'index1': value1, 'index2':value2,...}, ignore_index=True)
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Lucia
29 Aug 2016
1>>> df = pd.DataFrame([[1, 2], [3, 4]], columns=list('AB'))
2>>> df
3   A  B
40  1  2
51  3  4
6>>> df2 = pd.DataFrame([[5, 6], [7, 8]], columns=list('AB'))
7>>> df.append(df2)
8   A  B
90  1  2
101  3  4
110  5  6
121  7  8
13
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Jessica
05 Apr 2018
1# Basic syntax:
2import pandas as pd
3appended_dataframe = dataframe_1.append(dataframe_2)
4# or:
5appended_dataframe = pd.concat([dataframe_1, dataframe_2]) 
6
7# Example usage:
8dataframe_1 = pd.DataFrame([[1, 2], [3, 4]], columns=list('AB'))
9dataframe_2 = pd.DataFrame([[5, 6], [7, 8]], columns=list('AB'))
10appended_dataframe = dataframe_1.append(dataframe_2)
11print(appended_dataframe)
12   A  B
130  1  2
141  3  4
150  5  6
161  7  8
17
18# Note, add "ignore_index = False" if you want new sequential row indices
19# Note, append does not modify the dataframes in place, which is why
20#	running just dataframe_1.append(dataframe_2) doesn't change
21#	dataframe_1
22# Note, if the column names aren't the same, the dataframes will be
23#	appended with NaNs like:
24     A    B    C    D
250  1.0  2.0  NaN  NaN
261  3.0  4.0  NaN  NaN
270  NaN  NaN  5.0  6.0
281  NaN  NaN  7.0  8.0
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Debbie
30 Oct 2018
1>>> df = pd.DataFrame([[1, 2], [3, 4]], columns=list('AB'))
2>>> df
3   A  B
40  1  2
51  3  4
6>>> df2 = pd.DataFrame([[5, 6], [7, 8]], columns=list('AB'))
7>>> df.append(df2)
8   A  B
90  1  2
101  3  4
110  5  6
121  7  8
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