doc41main2['MDOCNO'] == '241128' or doc41main2['MDOCNO'] == 241128 ?

[maya413]

System Info

QUERY

盘点数值:241128, 自营成本=(初期库存金额+进货金额-退货金额)-期末库存金额, 这次的自营成本有多少？

Variable dfs: list[pd.DataFrame] is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.

Generate python code and return full updated code:
2024-12-31 13:20:20 [INFO] Executing Step 3: CodeGenerator
2024-12-31 13:20:44 [INFO] Prompt used:
None

2024-12-31 13:20:44 [INFO] Code generated:
```
# TODO: import the required dependencies
import pandas as pd

Write code here

Access the relevant dataframes

inventory_cash_record2 = dfs[5]
supplier_inout_record2 = dfs[4]
doc41main2 = dfs[2]

Filter dataframes based on the provided MDOCNO '241128'

filtered_doc = doc41main2[doc41main2['MDOCNO'] == '241128']
filtered_cash_records = inventory_cash_record2[inventory_cash_record2['master_id'].isin(filtered_doc['id'])]
filtered_supplier_records = supplier_inout_record2[supplier_inout_record2['master_id'].isin(filtered_doc['id'])]

Calculate initial inventory amount, purchase amount, return amount, and final inventory amount

initial_inventory_amount = filtered_doc['DSC'].iloc[0] if not filtered_doc['DSC'].iloc[0].isdigit() else float(filtered_doc['DSC'].iloc[0])
purchase_amount = filtered_supplier_records[filtered_supplier_records['mark'] == '进货']['amount'].sum()
return_amount = -filtered_supplier_records[filtered_supplier_records['mark'] == '退货']['amount'].sum()
final_inventory_amount = filtered_cash_records['receipt_amount'].sum()

Calculate the self-operated cost

self_operated_cost = (initial_inventory_amount + purchase_amount - return_amount) - final_inventory_amount

Declare result var:

result = {
"type": "number",
"value": self_operated_cost
}
```

2024-12-31 13:20:44 [INFO] Executing Step 4: CachePopulation
2024-12-31 13:20:44 [INFO] Executing Step 5: CodeCleaning
2024-12-31 13:20:44 [INFO]
Code running:

inventory_cash_record2 = dfs[5]
supplier_inout_record2 = dfs[4]
doc41main2 = dfs[2]
filtered_doc = doc41main2[doc41main2['MDOCNO'] == '241128']
filtered_cash_records = inventory_cash_record2[inventory_cash_record2['master_id'].isin(filtered_doc['id'])]
filtered_supplier_records = supplier_inout_record2[supplier_inout_record2['master_id'].isin(filtered_doc['id'])]
initial_inventory_amount = filtered_doc['DSC'].iloc[0] if not filtered_doc['DSC'].iloc[0].isdigit() else float(filtered_doc['DSC'].iloc[0])
purchase_amount = filtered_supplier_records[filtered_supplier_records['mark'] == '进货']['amount'].sum()
return_amount = -filtered_supplier_records[filtered_supplier_records['mark'] == '退货']['amount'].sum()
final_inventory_amount = filtered_cash_records['receipt_amount'].sum()
self_operated_cost = initial_inventory_amount + purchase_amount - return_amount - final_inventory_amount
result = {'type': 'number', 'value': self_operated_cost}
        ```
2024-12-31 13:20:44 [INFO] Executing Step 6: CodeExecution
2024-12-31 13:20:44 [ERROR] Failed with error: Traceback (most recent call last):
  File "D:\conda_env\chucansvn\lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
    result = self.execute_code(code_to_run, code_context)
  File "D:\conda_env\chucansvn\lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
    exec(code, environment)
  File "<string>", line 7, in <module>
  File "D:\conda_env\chucansvn\lib\site-packages\pandas\core\indexing.py", line 1073, in __getitem__
    return self._getitem_axis(maybe_callable, axis=axis)
  File "D:\conda_env\chucansvn\lib\site-packages\pandas\core\indexing.py", line 1625, in _getitem_axis
    self._validate_integer(key, axis)
  File "D:\conda_env\chucansvn\lib\site-packages\pandas\core\indexing.py", line 1557, in _validate_integer
    raise IndexError("single positional indexer is out-of-bounds")
IndexError: single positional indexer is out-of-bounds
"MDOCNO" is varchar(12) type in the database, and the code generated by llm is generated according to varchar(12), and the "MDOCNO" in this dfs[2] is int64-bit type, how to change it?

### 🐛 Describe the bug

### QUERY
 盘点数值:241128, 自营成本=(初期库存金额+进货金额-退货金额)-期末库存金额, 这次的自营成本有多少？

Variable `dfs: list[pd.DataFrame]` is already declared.

At the end, declare "result" variable as a dictionary of type and value.

If you are asked to plot a chart, use "matplotlib" for charts, save as png.


Generate python code and return full updated code:
2024-12-31 13:20:20 [INFO] Executing Step 3: CodeGenerator
2024-12-31 13:20:44 [INFO] Prompt used:
            None
            
2024-12-31 13:20:44 [INFO] Code generated:
            ```
            # TODO: import the required dependencies
import pandas as pd

# Write code here
# Access the relevant dataframes
inventory_cash_record2 = dfs[5]
supplier_inout_record2 = dfs[4]
doc41main2 = dfs[2]

# Filter dataframes based on the provided MDOCNO '241128'
filtered_doc = doc41main2[doc41main2['MDOCNO'] == '241128']
filtered_cash_records = inventory_cash_record2[inventory_cash_record2['master_id'].isin(filtered_doc['id'])]
filtered_supplier_records = supplier_inout_record2[supplier_inout_record2['master_id'].isin(filtered_doc['id'])]

# Calculate initial inventory amount, purchase amount, return amount, and final inventory amount
initial_inventory_amount = filtered_doc['DSC'].iloc[0] if not filtered_doc['DSC'].iloc[0].isdigit() else float(filtered_doc['DSC'].iloc[0])
purchase_amount = filtered_supplier_records[filtered_supplier_records['mark'] == '进货']['amount'].sum()
return_amount = -filtered_supplier_records[filtered_supplier_records['mark'] == '退货']['amount'].sum()
final_inventory_amount = filtered_cash_records['receipt_amount'].sum()

# Calculate the self-operated cost
self_operated_cost = (initial_inventory_amount + purchase_amount - return_amount) - final_inventory_amount

# Declare result var: 
result = {
    "type": "number",
    "value": self_operated_cost
}
            ```
            
2024-12-31 13:20:44 [INFO] Executing Step 4: CachePopulation
2024-12-31 13:20:44 [INFO] Executing Step 5: CodeCleaning
2024-12-31 13:20:44 [INFO] 
Code running:

inventory_cash_record2 = dfs[5]
supplier_inout_record2 = dfs[4]
doc41main2 = dfs[2]
filtered_doc = doc41main2[doc41main2['MDOCNO'] == '241128']
filtered_cash_records = inventory_cash_record2[inventory_cash_record2['master_id'].isin(filtered_doc['id'])]
filtered_supplier_records = supplier_inout_record2[supplier_inout_record2['master_id'].isin(filtered_doc['id'])]
initial_inventory_amount = filtered_doc['DSC'].iloc[0] if not filtered_doc['DSC'].iloc[0].isdigit() else float(filtered_doc['DSC'].iloc[0])
purchase_amount = filtered_supplier_records[filtered_supplier_records['mark'] == '进货']['amount'].sum()
return_amount = -filtered_supplier_records[filtered_supplier_records['mark'] == '退货']['amount'].sum()
final_inventory_amount = filtered_cash_records['receipt_amount'].sum()
self_operated_cost = initial_inventory_amount + purchase_amount - return_amount - final_inventory_amount
result = {'type': 'number', 'value': self_operated_cost}
```
2024-12-31 13:20:44 [INFO] Executing Step 6: CodeExecution
2024-12-31 13:20:44 [ERROR] Failed with error: Traceback (most recent call last):
File "D:\conda_env\chucansvn\lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 85, in execute
result = self.execute_code(code_to_run, code_context)
File "D:\conda_env\chucansvn\lib\site-packages\pandasai\pipelines\chat\code_execution.py", line 171, in execute_code
exec(code, environment)
File "", line 7, in
File "D:\conda_env\chucansvn\lib\site-packages\pandas\core\indexing.py", line 1073, in getitem
return self._getitem_axis(maybe_callable, axis=axis)
File "D:\conda_env\chucansvn\lib\site-packages\pandas\core\indexing.py", line 1625, in _getitem_axis
self._validate_integer(key, axis)
File "D:\conda_env\chucansvn\lib\site-packages\pandas\core\indexing.py", line 1557, in _validate_integer
raise IndexError("single positional indexer is out-of-bounds")
IndexError: single positional indexer is out-of-bounds
"MDOCNO" is varchar(12) type in the database, and the code generated by llm is generated according to varchar(12), and the "MDOCNO" in this dfs[2] is int64-bit type, how to change it?

[dosubot]

Hey there, @maya413! I'm here to help you out with any bugs, questions, or contributions you have. Let's tackle this together!

To resolve the issue with the MDOCNO column type mismatch, you need to ensure that the comparison is done with the correct data type. Since MDOCNO is stored as an int64 in the DataFrame doc41main2, you should compare it with an integer value. Here's how you can modify the code:

# Access the relevant dataframes
inventory_cash_record2 = dfs[5]
supplier_inout_record2 = dfs[4]
doc41main2 = dfs[2]

# Convert the comparison value to an integer
mdocno_value = 241128

# Filter dataframes based on the provided MDOCNO
filtered_doc = doc41main2[doc41main2['MDOCNO'] == mdocno_value]
filtered_cash_records = inventory_cash_record2[inventory_cash_record2['master_id'].isin(filtered_doc['id'])]
filtered_supplier_records = supplier_inout_record2[supplier_inout_record2['master_id'].isin(filtered_doc['id'])]

# Calculate initial inventory amount, purchase amount, return amount, and final inventory amount
initial_inventory_amount = float(filtered_doc['DSC'].iloc[0]) if not filtered_doc['DSC'].iloc[0].isdigit() else float(filtered_doc['DSC'].iloc[0])
purchase_amount = filtered_supplier_records[filtered_supplier_records['mark'] == '进货']['amount'].sum()
return_amount = -filtered_supplier_records[filtered_supplier_records['mark'] == '退货']['amount'].sum()
final_inventory_amount = filtered_cash_records['receipt_amount'].sum()

# Calculate the self-operated cost
self_operated_cost = (initial_inventory_amount + purchase_amount - return_amount) - final_inventory_amount

# Declare result var
result = {
    "type": "number",
    "value": self_operated_cost
}

This change ensures that the MDOCNO value is treated as an integer, which matches the data type in the DataFrame, thus preventing the IndexError.

To continue talking to Dosu, mention @dosu.

---

<sup>Help Dosu learn! Give it feedback: Great Response | Irrelevant Answer | Incorrect Sources | Too Verbose | Hallucination | Other</sup>