Python: Combining DataFrames (append, concat and join)

df1.append(df2) -

• Add rows in df1 to the end of df2 (columns should be identical)
• Use the append() method to stack one DataFrame (df1) on top of another DataFrame (df2).
• The DataFrames should have identical column names.
• Returns a new DataFrame with the combined rows.

Example:

import pandas as pd

data1 = {'A': [1, 2, 3], 'B': [4, 5, 6]}
data2 = {'A': [7, 8, 9], 'B': [10, 11, 12]}

df1 = pd.DataFrame(data1)
df2 = pd.DataFrame(data2)

combined_df = df1.append(df2)

# Resulting DataFrame (combined_df):
#    A   B
# 0  1   4
# 1  2   5
# 2  3   6
# 0  7  10
# 1  8  11
# 2  9  12

pd.concat([df1, df2], axis=1)

• Add columns in df1 to the end of df2 (rows should be identical)
• Use the concat() function to concatenate DataFrames (df1 and df2) horizontally along columns.
• The DataFrames should have identical row indices.
• Specify axis=1 to concatenate columns.

Example:

import pandas as pd

data1 = {'A': [1, 2, 3], 'B': [4, 5, 6]}
data2 = {'C': [7, 8, 9], 'D': [10, 11, 12]}

df1 = pd.DataFrame(data1)
df2 = pd.DataFrame(data2)
concatenated_df = pd.concat([df1, df2], axis=1)

# Resulting DataFrame (concatenated_df):
#    A  B  C   D
# 0  1  4  7  10
# 1  2  5  8  11
# 2  3  6  9  12

df1.join(df2, on='col1', how='inner')

• SQL-style inner join based on 'col1'
• Use the join() method to perform a SQL-style inner join between two DataFrames (df1 and df2) based on a common column ('col1').
• You can specify different types of joins (inner, outer, left, right) using the how parameter.

Example:

import pandas as pd

data1 = {'ID': [1, 2, 3], 'Name': ['Alice', 'Bob', 'Charlie']}
data2 = {'ID': [2, 3, 4], 'Age': [25, 30, 28]}
df1 = pd.DataFrame(data1)
df2 = pd.DataFrame(data2)
merged_df = df1.join(df2.set_index('ID'), on='ID', how='inner')

# Resulting DataFrame (merged_df):
#    ID     Name  Age
# 1   2      Bob   25
# 2   3  Charlie   30

These examples demonstrate how to combine DataFrames in various ways, either by appending rows, concatenating columns, or performing SQL-style joins based on common columns.