Answers for "concatenate dataframe pandas"

1

pandas concat series into dataframe

In [1]: s1 = pd.Series([1, 2], index=['A', 'B'], name='s1')

In [2]: s2 = pd.Series([3, 4], index=['A', 'B'], name='s2')

In [3]: pd.concat([s1, s2], axis=1)
Out[3]:
   s1  s2
A   1   3
B   2   4

In [4]: pd.concat([s1, s2], axis=1).reset_index()
Out[4]:
  index  s1  s2
0     A   1   3
1     B   2   4
Posted by: Guest on March-08-2021
2

joins in pandas

pd.merge(product,customer,how='inner',left_on=['Product_ID','Seller_City'],right_on=['Product_ID','City'])
Posted by: Guest on May-31-2020
3

Joins with another DataFrame

# Joins with another DataFrame

df.join(df2, df.name == df2.name, 'outer').select(
  df.name, df2.height).collect()
# [Row(name=None, height=80), Row(name=u'Bob', height=85), Row(
#   name=u'Alice', height=None)]

df.join(df2, 'name', 'outer').select('name', 'height').collect()
# [Row(name=u'Tom', height=80), Row(name=u'Bob', height=85), Row(
#   name=u'Alice', height=None)]

cond = [df.name == df3.name, df.age == df3.age]
df.join(df3, cond, 'outer').select(df.name, df3.age).collect()
# [Row(name=u'Alice', age=2), Row(name=u'Bob', age=5)]

df.join(df2, 'name').select(df.name, df2.height).collect()
# Row(name=u'Bob', height=85)]

df.join(df4, ['name', 'age']).select(df.name, df.age).collect()
# [Row(name=u'Bob', age=5)]
Posted by: Guest on April-20-2020
0

concat dataframe pandas

# provide list of dataframes 
res = pd.concat([df1, df2])
Posted by: Guest on August-14-2021
0

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)
Posted by: Guest on June-29-2020
0

df concatenate df

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)
Posted by: Guest on December-31-2020

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