pandas merge python
import pandas as pd
df1 = pd.DataFrame({'lkey': ['foo', 'bar', 'baz', 'foo'],
'value': [1, 2, 3, 5]})
df2 = pd.DataFrame({'rkey': ['foo', 'bar', 'baz', 'foo'],
'value': [5, 6, 7, 8]})
df1.merge(df2, left_on='lkey', right_on='rkey')merge dataframe pandas
>>> df1.merge(df2, left_on='lkey', right_on='rkey')
lkey value_x rkey value_y
0 foo 1 foo 5
1 foo 1 foo 8
2 foo 5 foo 5
3 foo 5 foo 8
4 bar 2 bar 6
5 baz 3 baz 7merge in python
def merge(array, left_index, right_index, middle):
# Make copies of both arrays we're trying to merge
# The second parameter is non-inclusive, so we have to increase by 1
left_copy = array[left_index:middle + 1]
right_copy = array[middle+1:right_index+1]
# Initial values for variables that we use to keep
# track of where we are in each array
left_copy_index = 0
right_copy_index = 0
sorted_index = left_index
# Go through both copies until we run out of elements in one
while left_copy_index < len(left_copy) and right_copy_index < len(right_copy):
# If our left_copy has the smaller element, put it in the sorted
# part and then move forward in left_copy (by increasing the pointer)
if left_copy[left_copy_index] <= right_copy[right_copy_index]:
array[sorted_index] = left_copy[left_copy_index]
left_copy_index = left_copy_index + 1
# Opposite from above
else:
array[sorted_index] = right_copy[right_copy_index]
right_copy_index = right_copy_index + 1
# Regardless of where we got our element from
# move forward in the sorted part
sorted_index = sorted_index + 1
# We ran out of elements either in left_copy or right_copy
# so we will go through the remaining elements and add them
while left_copy_index < len(left_copy):
array[sorted_index] = left_copy[left_copy_index]
left_copy_index = left_copy_index + 1
sorted_index = sorted_index + 1
while right_copy_index < len(right_copy):
array[sorted_index] = right_copy[right_copy_index]
right_copy_index = right_copy_index + 1
sorted_index = sorted_index + 1Copyright © 2021 Codeinu
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