8 examples of 'merge in pandas' in Python

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29def _concat(df, type):
30 if df is None:
31 df = pd.DataFrame(_object_blocks[type])
32 else:
33 _df = pd.DataFrame(_object_blocks[type])
34 df = pd.concat([df, _df], sort=True)
35 return df
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332def merge_datasets(self, other):
333 """
334 This operation combines two dataframes into one new DataFrame.
335 If the operation is combining two SpatialDataFrames, the
336 geometry_type must match.
337 """
338 if isinstance(other, SpatialDataFrame) and \
339 other.geometry_type == self.geometry_type:
340 return pd.concat(objs=[self, other], axis=0)
341 elif isinstance(other, DataFrame):
342 return pd.concat(objs=[self, other], axis=0)
343 elif isinstance(other, Series):
344 self['merged_datasets'] = other
345 elif isinstance(other, SpatialDataFrame) and \
346 other.geometry_type != self.geometry_type:
347 raise ValueError("Spatial DataFrames must have the same geometry type.")
348 else:
349 raise ValueError("Merge datasets cannot merge types %s" % type(other))
6def default_merger(x, y):
7 import pandas as pd
8 return pd.concat([x, y])
813def merge(old_cols, new_cols):
814 return old_cols + new_cols
142def append_data(df1, df2):
143 '''
144 Append df2 to df1
145 '''
146 df = pd.concat((df1, df2))
147 return df.groupby(df.index).first()
51def random_merge(A, B, N=20, on='AnswerId', key='key', n='n'):
52 """Pair all rows of A with 1 matching row on "on" and N-1 random rows from B
53 """
54 assert key not in A and key not in B
55 X = A.copy()
56 X[key] = A[on]
57 Y = B.copy()
58 Y[key] = B[on]
59 match = X.merge(Y, on=key).drop(key, axis=1)
60 match[n] = 0
61 df_list = [match]
62 for i in A.index:
63 X = A.loc[[i]]
64 Y = B[B[on] != X[on].iloc[0]].sample(N-1)
65 X[key] = 1
66 Y[key] = 1
67 Z = X.merge(Y, how='outer', on=key).drop(key, axis=1)
68 Z[n] = range(1, N)
69 df_list.append(Z)
70 df = pd.concat(df_list, ignore_index=True)
71 return df
474def full_merge_of_existing_series(old_series, new_series):
475 """
476 Merges old data with new data.
477 Any Nan in the existing data will be replaced (be careful!)
478
479 :param old_data: pd.Series
480 :param new_data: pd.Series
481
482 :returns: pd.Series
483 """
484 if len(old_series)==0:
485 return new_series
486 if len(new_series)==0:
487 return old_series
488
489 joint_data = pd.concat([old_series, new_series], axis=1)
490 joint_data.columns = ['original', 'new']
491
492 # fill to the left
493 joint_data_filled_across = joint_data.bfill(1)
494 merged_data = joint_data_filled_across['original']
495
496 return merged_data
88def merge_lvj_dfs(df1, df2, how='outer'):
89 """
90 Merge two data frames on lvj indices.
91
92 By default, uses the union of the keys (an "outer" join).
93 """
94 merged = pd.merge(df1, df2, how=how, left_index=True, right_index=True)
95 merged.fillna(0, inplace=True)
96 return merged

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