add more docs and test cases

Author: patrick

docs/pandas/Tablular-data.png

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+# Pandas-30minutes For QA
+
+**What is Pandas?**
+> **Python lib to handle ***data***.**
+
+## 1.Talking about data 
+
+**What kind of data Pandas to handle:**
+
+- **DataFrame**: Tablular data;header/column/row data
+- **Series**: each column in a dataframe is series
+
+---
+
+## 1.1 Examples for DataFrame and Series data
+
+1. **DataFrame**:
+
+![img.png](dataframe.png)
+
+---
+
+```python
+df_cr= pd.DataFrame({
+  "Name":["Braund, Mr. Owen Harris",
+            "Allen, Mr. William Henry",
+            "Bonnell, Miss. Elizabeth",],
+  "Age": [22, 35, 58],
+        "Sex": ["male", "male", "female"],
+})
+print(df_cr)
+```
+---
+
+2. **Series**: each column in a dataframe is series
+
+![img_1.png](series-data.png)
+---
+
+```python
+print(df_cr["Age"])
+print(df_cr['Age'].max())
+print(df_cr['Age'].min())
+print(df_cr['Age'].mean())
+```
+---
+
+## 2.Read and Write Tablular Data
+Tabluar data:
+
+![img_2.png](Tablular-data.png)
+
+![img_3.png](excel-data.png)
+
+---
+
+```python
+
+```
+
+
+## 3. Select Subset of Dataframe
+
+What does subset mean?
+
+![img_4.png](subset-1.png)
+![img_5.png](subset-2.png)
+![img_6.png](subset-3.png)
+
+--- 
+
+
+## 5. Create Plot 
+
+![img_7.png](plot.png)
+---
+
+## 6. Read Excel/CSV data to Python object
+
+![img.png](structured_data.png)
+
+```python
+import pandas as pd
+from pydantic import BaseModel,Field,ConfigDict
+class UnitInfoRawModel(BaseModel):
+    unit_name: str = Field("", alias='单位名')
+    unit_symbol: str = Field("", alias='单位符号')
+    unit_symbol_latex: str = Field("", alias='单位符号LaTex')
+    unit_group_name: str = Field("", alias='单位组名称')
+    base_unit: str = Field("", alias='基准单位')
+    conversion_factor: None|str |float = Field("", alias='换算系数')
+
+    model_config = ConfigDict(
+        arbitrary_types_allowed=True,
+        populate_by_name=True,
+        use_enum_values=True,
+    )
+
+df = pd.read_excel("x.xlsx", na_filter=False, na_values=['NaN'])
+t_list = []
+for index, row in df.iterrows():
+        t_list.append(UnitInfoRawModel(**row.to_dict()))
+print(t_list)
+```