feat: add pandas solution to lc problem: No.0570 (#1892)

Author: nrhitik

solution/0500-0599/0570.Managers with at Least 5 Direct Reports/README.md

@@ -81,4 +81,31 @@ FROM
         USING (id);
 ```
 
+### **Pandas**
+
+```python
+import pandas as pd
+
+
+def find_managers(employee: pd.DataFrame) -> pd.DataFrame:
+    # Group the employees by managerId and count the number of direct reports
+    manager_report_count = (
+        employee.groupby("managerId").size().reset_index(name="directReports")
+    )
+
+    # Filter managers with at least five direct reports
+    result = manager_report_count[manager_report_count["directReports"] >= 5]
+
+    # Merge with the Employee table to get the names of these managers
+    result = result.merge(
+        employee[["id", "name"]], left_on="managerId", right_on="id", how="inner"
+    )
+
+    # Select only the 'name' column and drop the 'id' and 'directReports' columns
+    result = result[["name"]]
+
+    return result
+
+```
+
 <!-- tabs:end -->

solution/0500-0599/0570.Managers with at Least 5 Direct Reports/README_EN.md

@@ -77,4 +77,31 @@ FROM
         USING (id);
 ```
 
+### **Pandas**
+
+```python
+import pandas as pd
+
+
+def find_managers(employee: pd.DataFrame) -> pd.DataFrame:
+    # Group the employees by managerId and count the number of direct reports
+    manager_report_count = (
+        employee.groupby("managerId").size().reset_index(name="directReports")
+    )
+
+    # Filter managers with at least five direct reports
+    result = manager_report_count[manager_report_count["directReports"] >= 5]
+
+    # Merge with the Employee table to get the names of these managers
+    result = result.merge(
+        employee[["id", "name"]], left_on="managerId", right_on="id", how="inner"
+    )
+
+    # Select only the 'name' column and drop the 'id' and 'directReports' columns
+    result = result[["name"]]
+
+    return result
+
+```
+
 <!-- tabs:end -->

solution/0500-0599/0570.Managers with at Least 5 Direct Reports/Solution.py

@@ -0,0 +1,21 @@
+import pandas as pd
+
+
+def find_managers(employee: pd.DataFrame) -> pd.DataFrame:
+    # Group the employees by managerId and count the number of direct reports
+    manager_report_count = (
+        employee.groupby("managerId").size().reset_index(name="directReports")
+    )
+
+    # Filter managers with at least five direct reports
+    result = manager_report_count[manager_report_count["directReports"] >= 5]
+
+    # Merge with the Employee table to get the names of these managers
+    result = result.merge(
+        employee[["id", "name"]], left_on="managerId", right_on="id", how="inner"
+    )
+
+    # Select only the 'name' column and drop the 'id' and 'directReports' columns
+    result = result[["name"]]
+
+    return result