import pandas as pd
df1 = pd.DataFrame({'key': ['A', 'B', 'C', 'D'],
'value1': [1, 2, 3, 4]})
df2 = pd.DataFrame({'key': ['B', 'D', 'E', 'F'],
'value2': [5, 6, 7, 8]})
merged_df = pd.merge(df1, df2, on='key')
print(merged_df)
key value1 value2
0 B 2 5
1 D 4 6
import pandas as pd
df1 = pd.DataFrame({'value1': [1, 2, 3, 4]},
index=['A', 'B', 'C', 'D'])
df2 = pd.DataFrame({'value2': [5, 6, 7, 8]},
index=['B', 'D', 'E', 'F'])
joined_df = df1.join(df2)
print(joined_df)
value1 value2
A 1 NaN
B 2 5.0
C 3 NaN
D 4 6.0
import pandas as pd
df = pd.DataFrame({'key': ['A', 'B', 'A', 'B'],
'value': [1, 2, 3, 4]})
summarized_df = df.groupby('key').sum()
print(summarized_df)
value
key
A 4
B 6
import pandas as pd
df = pd.DataFrame({'key': ['A', 'A', 'B', 'B'],
'category': ['x', 'y', 'x', 'y'],
'value': [1, 2, 3, 4]})
pivoted_df = df.pivot(index='key', columns='category', values='value')
print(pivoted_df)
category x y
key
A 1 2
B 3 4
import pandas as pd
df = pd.DataFrame({'key': ['A', 'B'],
'value1': [1, 2],
'value2': [3, 4]})
stacked_df = df.stack().reset_index()
print(stacked_df)
level_0 level_1 0
0 key 0 A
1 key 1 B
2 value1 0 1
3 value1 1 2
4 value2 0 3
5 value2 1 4
