feat: add pandas solutions to lc problems: No.0185,0196 (doocs#1873)

solution/0100-0199/0185.Department Top Three Salaries/README.md

@@ -139,4 +139,30 @@ FROM
 WHERE rk <= 3;
 ```
 
+### **Pandas**
+
+```python
+import pandas as pd
+
+
+def top_three_salaries(
+    employee: pd.DataFrame, department: pd.DataFrame
+) -> pd.DataFrame:
+    salary_cutoff = (
+        employee.drop_duplicates(["salary", "departmentId"])
+        .groupby("departmentId")["salary"]
+        .nlargest(3)
+        .groupby("departmentId")
+        .min()
+    )
+    employee["Department"] = department.set_index("id")["name"][
+        employee["departmentId"]
+    ].values
+    employee["cutoff"] = salary_cutoff[employee["departmentId"]].values
+    return employee[employee["salary"] >= employee["cutoff"]].rename(
+        columns={"name": "Employee", "salary": "Salary"}
+    )[["Department", "Employee", "Salary"]]
+
+```
+
 <!-- tabs:end -->

solution/0100-0199/0185.Department Top Three Salaries/README_EN.md

@@ -135,4 +135,30 @@ FROM
 WHERE rk <= 3;
 ```
 
+### **Pandas**
+
+```python
+import pandas as pd
+
+
+def top_three_salaries(
+    employee: pd.DataFrame, department: pd.DataFrame
+) -> pd.DataFrame:
+    salary_cutoff = (
+        employee.drop_duplicates(["salary", "departmentId"])
+        .groupby("departmentId")["salary"]
+        .nlargest(3)
+        .groupby("departmentId")
+        .min()
+    )
+    employee["Department"] = department.set_index("id")["name"][
+        employee["departmentId"]
+    ].values
+    employee["cutoff"] = salary_cutoff[employee["departmentId"]].values
+    return employee[employee["salary"] >= employee["cutoff"]].rename(
+        columns={"name": "Employee", "salary": "Salary"}
+    )[["Department", "Employee", "Salary"]]
+
+```
+
 <!-- tabs:end -->

solution/0100-0199/0185.Department Top Three Salaries/Solution.py

@@ -0,0 +1,20 @@
+import pandas as pd
+
+
+def top_three_salaries(
+    employee: pd.DataFrame, department: pd.DataFrame
+) -> pd.DataFrame:
+    salary_cutoff = (
+        employee.drop_duplicates(["salary", "departmentId"])
+        .groupby("departmentId")["salary"]
+        .nlargest(3)
+        .groupby("departmentId")
+        .min()
+    )
+    employee["Department"] = department.set_index("id")["name"][
+        employee["departmentId"]
+    ].values
+    employee["cutoff"] = salary_cutoff[employee["departmentId"]].values
+    return employee[employee["salary"] >= employee["cutoff"]].rename(
+        columns={"name": "Employee", "salary": "Salary"}
+    )[["Department", "Employee", "Salary"]]

solution/0100-0199/0196.Delete Duplicate Emails/README.md

@@ -97,4 +97,19 @@ WHERE
     p1.id < p2.id;
 ```
 
+### **Pandas**
+
+```python
+import pandas as pd
+
+
+# Modify Person in place
+def delete_duplicate_emails(person: pd.DataFrame) -> None:
+    # Sort the rows based on id (Ascending order)
+    person.sort_values(by="id", ascending=True, inplace=True)
+    # Drop the duplicates based on email.
+    person.drop_duplicates(subset="email", keep="first", inplace=True)
+
+```
+
 <!-- tabs:end -->

solution/0100-0199/0196.Delete Duplicate Emails/README_EN.md

@@ -93,4 +93,19 @@ WHERE
     p1.id < p2.id;
 ```
 
+### **Pandas**
+
+```python
+import pandas as pd
+
+
+# Modify Person in place
+def delete_duplicate_emails(person: pd.DataFrame) -> None:
+    # Sort the rows based on id (Ascending order)
+    person.sort_values(by="id", ascending=True, inplace=True)
+    # Drop the duplicates based on email.
+    person.drop_duplicates(subset="email", keep="first", inplace=True)
+
+```
+
 <!-- tabs:end -->

solution/0100-0199/0196.Delete Duplicate Emails/Solution.py

@@ -0,0 +1,9 @@
+import pandas as pd
+
+
+# Modify Person in place
+def delete_duplicate_emails(person: pd.DataFrame) -> None:
+    # Sort the rows based on id (Ascending order)
+    person.sort_values(by="id", ascending=True, inplace=True)
+    # Drop the duplicates based on email.
+    person.drop_duplicates(subset="email", keep="first", inplace=True)