Pivot Tablet
In [9]:
# Basic Pivot
import pandas as pd
df = pd.DataFrame({
'Date': ['2024-01-01', '2024-01-02', '2024-01-03'],
'City': ['New York', 'Los Angeles', 'Chicago'],
'Temperature': [30, 22, 25]
})
pivot_df = df.pivot(index='Date', columns='City', values='Temperature')
print("Source")
print(df)
print("Pivot")
print(pivot_df)
Source
Date City Temperature
0 2024-01-01 New York 30
1 2024-01-02 Los Angeles 22
2 2024-01-03 Chicago 25
Pivot
City Chicago Los Angeles New York
Date
2024-01-01 NaN NaN 30.0
2024-01-02 NaN 22.0 NaN
2024-01-03 25.0 NaN NaN
In [10]:
# Pivot with MultiIndex
import pandas as pd
df = pd.DataFrame({
'Date': ['2024-01-01', '2024-01-01', '2024-01-02', '2024-01-02'],
'City': ['New York', 'Los Angeles', 'New York', 'Los Angeles'],
'Temperature': [30, 22, 28, 24]
})
pivot_df = df.pivot(index='Date', columns='City', values='Temperature')
print("Source")
print(df)
print("Pivot")
print(pivot_df)
Source
Date City Temperature
0 2024-01-01 New York 30
1 2024-01-01 Los Angeles 22
2 2024-01-02 New York 28
3 2024-01-02 Los Angeles 24
Pivot
City Los Angeles New York
Date
2024-01-01 22 30
2024-01-02 24 28
In [11]:
# Pivot with Aggregation
import pandas as pd
df = pd.DataFrame({
'Date': ['2024-01-01', '2024-01-01', '2024-01-02', '2024-01-02'],
'City': ['New York', 'Los Angeles', 'New York', 'Los Angeles'],
'Temperature': [30, 22, 28, 24]
})
pivot_table_df = df.pivot_table(index='Date', columns='City', values='Temperature', aggfunc='mean')
print("Source")
print(df)
print("Pivot")
print(pivot_table_df)
Source
Date City Temperature
0 2024-01-01 New York 30
1 2024-01-01 Los Angeles 22
2 2024-01-02 New York 28
3 2024-01-02 Los Angeles 24
Pivot
City Los Angeles New York
Date
2024-01-01 22.0 30.0
2024-01-02 24.0 28.0
In [12]:
# Pivot with Multiple Values
import pandas as pd
df = pd.DataFrame({
'Date': ['2024-01-01', '2024-01-01', '2024-01-02', '2024-01-02'],
'City': ['New York', 'Los Angeles', 'New York', 'Los Angeles'],
'Temperature': [30, 22, 28, 24],
'Humidity': [55, 60, 50, 65]
})
pivot_df = df.pivot(index='Date', columns='City', values=['Temperature', 'Humidity'])
print("Source")
print(df)
print("Pivot")
print(pivot_df)
Source
Date City Temperature Humidity
0 2024-01-01 New York 30 55
1 2024-01-01 Los Angeles 22 60
2 2024-01-02 New York 28 50
3 2024-01-02 Los Angeles 24 65
Pivot
Temperature Humidity
City Los Angeles New York Los Angeles New York
Date
2024-01-01 22 30 60 55
2024-01-02 24 28 65 50