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You are a Data Analyst at Salesforce. The Sales team wants a pricing matrix showing all possible plan and company size combinations. This will help them quickly reference which plans are available for different company sizes. Use a cross join to generate every combination of plan and size bucket.
| Column Name | Type |
|---|---|
| plan_id | int64 |
| plan_code | object |
| plan_name | object |
| billing_period |
You are a Data Analyst at Salesforce. The Sales team wants a pricing matrix showing all possible plan and company size combinations. This will help them quickly reference which plans are available for different company sizes. Use a cross join to generate every combination of plan and size bucket.
| Column Name | Type |
|---|---|
| plan_id | int64 |
| plan_code | object |
| plan_name | object |
| billing_period |
| object |
| object |
| base_price_cents | int64 |
| base_price_cents | int64 |
| per_seat_cents | int64 |
| per_seat_cents | int64 |
| includes_overage | int64 |
| includes_overage | int64 |
| overage_per_unit_cents | int64 |
| overage_per_unit_cents | int64 |
| trial_days | int64 |
| trial_days | int64 |
| is_self_serve | int64 |
| is_self_serve | int64 |
| status | object |
| status | object |
| currency | object |
| currency | object |
| created_at | object |
| created_at | object |
| Column Name | Type |
|---|---|
| org_id | int64 |
| org_code | object |
| org_name | object |
| industry | object |
| size_bucket | object |
| country | object |
| Column Name | Type |
|---|---|
| org_id | int64 |
| org_code | object |
| org_name | object |
| industry | object |
| size_bucket | object |
| country | object |
| plan_id | plan_code | plan_name | billing_period | base_price_cents | per_seat_cents | includes_overage | overage_per_unit_cents | trial_days | is_self_serve | status | currency | created_at |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 |
| plan_id | plan_code | plan_name | billing_period | base_price_cents | per_seat_cents | includes_overage | overage_per_unit_cents | trial_days | is_self_serve | status | currency | created_at |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 |
| org_id | org_code | org_name | industry | size_bucket | country | state | city | primary_domain | status | created_at |
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | ORG00001 | Vivid Data | software |
| org_id | org_code | org_name | industry | size_bucket | country | state | city | primary_domain | status | created_at |
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | ORG00001 | Vivid Data | software |
| plan_id | plan_name | size_bucket |
|---|---|---|
| 1 | Free (Monthly) | enterprise |
| 1 | Free (Monthly) | mid |
| 1 | Free (Monthly) | small |
| 2 | Starter (Monthly) | enterprise |
| 2 | Starter (Monthly) | mid |
| plan_id | plan_name | size_bucket |
|---|---|---|
| 1 | Free (Monthly) | enterprise |
| 1 | Free (Monthly) | mid |
| 1 | Free (Monthly) | small |
| 2 | Starter (Monthly) | enterprise |
| 2 | Starter (Monthly) | mid |
Showing first 5 of 45 rows.
Showing first 5 of 45 rows.
1. DataFrames:
2. Cross Join:
3. Output:
1. DataFrames:
2. Cross Join:
3. Output:
| state | object |
| state | object |
| city | object |
| city | object |
| primary_domain | object |
| primary_domain | object |
| status | object |
| status | object |
| created_at | object |
| created_at | object |
| PLAN-FREE-MON |
| PLAN-FREE-MON |
| Free (Monthly) |
| Free (Monthly) |
| monthly |
| monthly |
| 0 |
| 0 |
| 0 |
| 0 |
| 0 |
| 0 |
| 0 |
| 0 |
| 14 |
| 14 |
| 1 |
| 1 |
| active |
| active |
| USD |
| USD |
| 2024-04-10 |
| 2024-04-10 |
| 2 | PLAN-STARTER-MON | Starter (Monthly) | monthly | 2900 | 900 | 0 | 0 | 14 | 1 | active | USD | 2024-05-12 |
| 2 | PLAN-STARTER-MON | Starter (Monthly) | monthly | 2900 | 900 | 0 | 0 | 14 | 1 | active | USD | 2024-05-12 |
| 3 | PLAN-STARTER-ANN | Starter (Annual) | annual | 29000 | 800 | 0 | 0 | 14 | 1 | active | USD | 2024-06-09 |
| 3 | PLAN-STARTER-ANN | Starter (Annual) | annual | 29000 | 800 | 0 | 0 | 14 | 1 | active | USD | 2024-06-09 |
| 4 | PLAN-PROFESSIONAL-MON | Professional (Monthly) | monthly | 7900 | 2500 | 1 | 25 | 14 | 1 | active | USD | 2024-09-24 |
| 4 | PLAN-PROFESSIONAL-MON | Professional (Monthly) | monthly | 7900 | 2500 | 1 | 25 | 14 | 1 | active | USD | 2024-09-24 |
| 5 | PLAN-PROFESSIONAL-ANN | Professional (Annual) | annual | 79000 | 2200 | 1 | 5 | 14 | 1 | active | USD | 2024-09-12 |
| 5 | PLAN-PROFESSIONAL-ANN | Professional (Annual) | annual | 79000 | 2200 | 1 | 5 | 14 | 1 | active | USD | 2024-09-12 |
| mid |
| mid |
| US |
| US |
| MA |
| MA |
| Boston |
| Boston |
| vividdata.app |
| vividdata.app |
| active |
| active |
| 2025-06-07 |
| 2025-06-07 |
| 2 | ORG00002 | Edge Software | fintech | small | US | TN | Nashville | edgesoftware.tech | active | 2024-12-11 |
| 2 | ORG00002 | Edge Software | fintech | small | US | TN | Nashville | edgesoftware.tech | active | 2024-12-11 |
| 3 | ORG00003 | Wind Works | devtools | small | US | CA | San Francisco | windworks.io | trial | 2025-02-22 |
| 3 | ORG00003 | Wind Works | devtools | small | US | CA | San Francisco | windworks.io | trial | 2025-02-22 |
| 4 | ORG00004 | Motion Dynamics | legaltech | enterprise | US | CA | Los Angeles | motiondynamics.ai | active | 2025-02-24 |
| 4 | ORG00004 | Motion Dynamics | legaltech | enterprise | US | CA | Los Angeles | motiondynamics.ai | active | 2025-02-24 |
| 5 | ORG00005 | Upward Intelligence | fintech | mid | US | TX | Houston | upwardintelligence.com | active | 2025-07-19 |
| 5 | ORG00005 | Upward Intelligence | fintech | mid | US | TX | Houston | upwardintelligence.com | active | 2025-07-19 |