Pandas ignore index
Code examples
append dataframe pandas
>>> df = pd.DataFrame([[1, 2], [3, 4]], columns=list('AB'))
>>> df
A B
0 1 2
1 3 4
>>> df2 = pd.DataFrame([[5, 6], [7, 8]], columns=list('AB'))
>>> df.append(df2)
A B
0 1 2
1 3 4
0 5 6
1 7 8
dataframe concatenate
# Pandas for Python
df['col1 & col2'] = df['col1']+df['col2']
#Output
#col1 col2 col1 & col2
#A1 A2 A1A2
#B1 B2 B1B2append to pandas dataframe
df = df.append({'index1': value1, 'index2':value2,...}, ignore_index=True)appending dataframes pandas
>>> df = pd.DataFrame([[1, 2], [3, 4]], columns=list('AB'))
>>> df
A B
0 1 2
1 3 4
>>> df2 = pd.DataFrame([[5, 6], [7, 8]], columns=list('AB'))
>>> df.append(df2)
A B
0 1 2
1 3 4
0 5 6
1 7 8pandas append index ignore
>>> df = pd.DataFrame([[1, 2], [3, 4]], columns=list('AB'))
>>> df2 = pd.DataFrame([[5, 6], [7, 8]], columns=list('AB'))
>>> df.append(df2, ignore_index=True)
A B
0 1 2
1 3 4
2 5 6
3 7 8pandas drop integer index
In [5055]: idx = np.ones(len(df.index), dtype=bool)
In [5057]: idx[rowindex] = False
In [5058]: df.iloc[idx] # or df.loc[idx]
Out[5058]:
A B C
2015-10-22 09:40:00 0.704959 0.995358 0.355915
2015-10-22 09:40:00 0.151127 0.398876 0.240856
2015-10-22 09:50:00 0.343456 0.513128 0.666625
2015-10-22 10:00:00 0.105908 0.130895 0.321981
concat two dataframe pandas python
In [1]: df1 = pd.DataFrame({'A': ['A0', 'A1', 'A2', 'A3'],
...: 'B': ['B0', 'B1', 'B2', 'B3'],
...: 'C': ['C0', 'C1', 'C2', 'C3'],
...: 'D': ['D0', 'D1', 'D2', 'D3']},
...: index=[0, 1, 2, 3])
...:
In [2]: df2 = pd.DataFrame({'A': ['A4', 'A5', 'A6', 'A7'],
...: 'B': ['B4', 'B5', 'B6', 'B7'],
...: 'C': ['C4', 'C5', 'C6', 'C7'],
...: 'D': ['D4', 'D5', 'D6', 'D7']},
...: index=[4, 5, 6, 7])
...:
In [3]: df3 = pd.DataFrame({'A': ['A8', 'A9', 'A10', 'A11'],
...: 'B': ['B8', 'B9', 'B10', 'B11'],
...: 'C': ['C8', 'C9', 'C10', 'C11'],
...: 'D': ['D8', 'D9', 'D10', 'D11']},
...: index=[8, 9, 10, 11])
...:
In [4]: frames = [df1, df2, df3]
In [5]: result = pd.concat(frames)
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