feat: add pandas solution to lc problem: No.0178 (doocs#1861)

Author: nrhitik

solution/0100-0199/0178.Rank Scores/README.md

@@ -122,4 +122,19 @@ FROM
     ) s;
 ```
 
+```python
+import pandas as pd
+
+
+def order_scores(scores: pd.DataFrame) -> pd.DataFrame:
+    # Use the rank method to assign ranks to the scores in descending order with no gaps
+    scores["rank"] = scores["score"].rank(method="dense", ascending=False)
+
+    # Drop id column & Sort the DataFrame by score in descending order
+    result_df = scores.drop("id", axis=1).sort_values(by="score", ascending=False)
+
+    return result_df
+
+```
+
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solution/0100-0199/0178.Rank Scores/README_EN.md

@@ -113,4 +113,19 @@ FROM
     ) s;
 ```
 
+```python
+import pandas as pd
+
+
+def order_scores(scores: pd.DataFrame) -> pd.DataFrame:
+    # Use the rank method to assign ranks to the scores in descending order with no gaps
+    scores["rank"] = scores["score"].rank(method="dense", ascending=False)
+
+    # Drop id column & Sort the DataFrame by score in descending order
+    result_df = scores.drop("id", axis=1).sort_values(by="score", ascending=False)
+
+    return result_df
+
+```
+
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solution/0100-0199/0178.Rank Scores/Solution.py

@@ -0,0 +1,11 @@
+import pandas as pd
+
+
+def order_scores(scores: pd.DataFrame) -> pd.DataFrame:
+    # Use the rank method to assign ranks to the scores in descending order with no gaps
+    scores["rank"] = scores["score"].rank(method="dense", ascending=False)
+
+    # Drop id column & Sort the DataFrame by score in descending order
+    result_df = scores.drop("id", axis=1).sort_values(by="score", ascending=False)
+
+    return result_df