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fix(editor): Editor run/save bug

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🔥1.Editor bug fix
🔥2.ChatExcel Stability optimization
This commit is contained in:
yhjun1026 2023-09-01 10:40:18 +08:00
parent 26716ddeb9
commit 7ae10a98f7
3 changed files with 65 additions and 47 deletions
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22
pilot/commands/disply_type/show_chart_gen.py
View File

@ -210,18 +210,22 @@ def response_bar_chart(speak: str, df: DataFrame) -> str:
data=df, x=x, y=sub_y_column, hue=hue, palette="Set2", ax=ax
)
else:
if len(num_colmns) >= 3:
can_use_columns = num_colmns[:3]
if len(num_colmns) > 5:
can_use_columns = num_colmns[:5]
else:
can_use_columns = num_colmns
sns.barplot(
data=df, x=x, y=y, hue=can_use_columns[0], palette="Set2", ax=ax
)
can_use_columns.append(y)
for sub_y_column in can_use_columns[1:]:
sns.barplot(
data=df, x=x, y=sub_y_column, hue=hue, palette="Set2", ax=ax
)
df_melted = pd.melt(
df,
id_vars=x,
value_vars=can_use_columns,
var_name="line",
value_name="Value",
)
sns.barplot(
data=df_melted, x=x, y="Value", hue="line", palette="Set2", ax=ax
)
else:
sns.barplot(data=df, x=x, y=y, hue=hue, palette="Set2", ax=ax)

5
pilot/scene/chat_data/chat_excel/excel_analyze/chat.py
View File

@ -104,4 +104,7 @@ class ChatExcel(BaseChat):
"speak": prompt_response.thoughts,
"df": self.excel_reader.get_df_by_sql_ex(prompt_response.sql),
}
return CFG.command_disply.call(prompt_response.display, **param)
if CFG.command_disply.get_command(prompt_response.display):
return CFG.command_disply.call(prompt_response.display, **param)
else:
return CFG.command_disply.call("response_table", **param)

85
pilot/scene/chat_data/chat_excel/excel_learning/test.py
View File

@ -157,7 +157,7 @@ if __name__ == "__main__":
# # colunms, datas = excel_reader.run( """ SELECT Year, SUM(Sales) AS Total_Sales FROM example GROUP BY Year ORDER BY Year; """)
# df = excel_reader.get_df_by_sql_ex(""" SELECT Segment, Country, SUM(Sales) AS Total_Sales, SUM(Profit) AS Total_Profit FROM example GROUP BY Segment, Country """)
df = excel_reader.get_df_by_sql_ex(
""" SELECT `明细`, `费用小计`, `支出小计` FROM yhj-zx limit 10"""
""" SELECT 大项, AVG(实际) AS 平均实际支出, AVG(已支出) AS 平均已支出 FROM yhj-zx GROUP BY 大项"""
)
for column_name in df.columns.tolist():
@ -203,44 +203,55 @@ if __name__ == "__main__":
# sns.barplot(df, x=x, y="Total_Profit", hue='Country', ax=ax)
# sns.catplot(data=df, x=x, y=y, hue='Country', kind='bar')
x, y, non_num_columns, num_colmns = data_pre_classification(df)
print(x, y, str(non_num_columns), str(num_colmns))
# x, y, non_num_columns, num_colmns = data_pre_classification(df)
# print(x, y, str(non_num_columns), str(num_colmns))
## 复杂折线图实现
if len(num_colmns) > 0:
num_colmns.append(y)
df_melted = pd.melt(
df, id_vars=x, value_vars=num_colmns, var_name="line", value_name="Value"
)
sns.lineplot(data=df_melted, x=x, y="Value", hue="line", ax=ax, palette="Set2")
else:
sns.lineplot(data=df, x=x, y=y, ax=ax, palette="Set2")
# hue = None
# ## 复杂柱状图实现
# x,y, non_num_columns, num_colmns =data_pre_classification(df)
# if len(non_num_columns) >= 1:
# hue = non_num_columns[0]
# if len(num_colmns)>=1:
# if hue:
# if len(num_colmns) >= 2:
# can_use_columns = num_colmns[:2]
# else:
# can_use_columns = num_colmns
# sns.barplot(data=df, x=x, y=y, hue=hue, palette="Set2", ax=ax)
# for sub_y_column in can_use_columns:
# sns.barplot(data=df, x=x, y=sub_y_column, hue=hue, palette="Set2", ax=ax)
# else:
# if len(num_colmns) >= 3:
# can_use_columns = num_colmns[:3]
# else:
# can_use_columns = num_colmns
# sns.barplot(data=df, x=x, y=y, hue=can_use_columns[0], palette="Set2", ax=ax)
#
# for sub_y_column in can_use_columns[1:]:
# sns.barplot(data=df, x=x, y=sub_y_column, hue=hue, palette="Set2", ax=ax)
# if len(num_colmns) > 0:
# num_colmns.append(y)
# df_melted = pd.melt(
# df, id_vars=x, value_vars=num_colmns, var_name="line", value_name="Value"
# )
# sns.lineplot(data=df_melted, x=x, y="Value", hue="line", ax=ax, palette="Set2")
# else:
# sns.barplot(data=df, x=x, y=y, hue=hue, palette="Set2", ax=ax)
# sns.lineplot(data=df, x=x, y=y, ax=ax, palette="Set2")
hue = None
## 复杂柱状图实现
x, y, non_num_columns, num_colmns = data_pre_classification(df)
if len(non_num_columns) >= 1:
hue = non_num_columns[0]
if len(num_colmns) >= 1:
if hue:
if len(num_colmns) >= 2:
can_use_columns = num_colmns[:2]
else:
can_use_columns = num_colmns
sns.barplot(data=df, x=x, y=y, hue=hue, palette="Set2", ax=ax)
for sub_y_column in can_use_columns:
sns.barplot(
data=df, x=x, y=sub_y_column, hue=hue, palette="Set2", ax=ax
)
else:
if len(num_colmns) > 5:
can_use_columns = num_colmns[:5]
else:
can_use_columns = num_colmns
can_use_columns.append(y)
df_melted = pd.melt(
df,
id_vars=x,
value_vars=can_use_columns,
var_name="line",
value_name="Value",
)
sns.barplot(
data=df_melted, x=x, y="Value", hue="line", palette="Set2", ax=ax
)
else:
sns.barplot(data=df, x=x, y=y, hue=hue, palette="Set2", ax=ax)
# # 转换 DataFrame 格式
# df_melted = pd.melt(df, id_vars=x, value_vars=['Total_Sales', 'Total_Profit'], var_name='line', value_name='y')