diff --git a/192. Word Frequency b/192. Word Frequency
new file mode 100644
index 0000000..603c653
--- /dev/null
+++ b/192. Word Frequency	
@@ -0,0 +1 @@
+tr -s ' ' '\n' < words.txt | sort | uniq -c | sort -nr | awk '{print $2, $1}'
diff --git a/197. Rising Temperature b/197. Rising Temperature
new file mode 100644
index 0000000..c28f849
--- /dev/null
+++ b/197. Rising Temperature	
@@ -0,0 +1,7 @@
+SELECT today.id
+FROM Weather yesterday 
+CROSS JOIN Weather today
+
+WHERE DATEDIFF(today.recordDate,yesterday.recordDate) = 1
+    AND today.temperature > yesterday.temperature
+;
diff --git a/Find Customer Referee b/Find Customer Referee
new file mode 100644
index 0000000..0739cc0
--- /dev/null
+++ b/Find Customer Referee	
@@ -0,0 +1,3 @@
+SELECT name 
+FROM Customer
+WHERE referee_id IS NULL OR referee_id != 2;
diff --git a/Print FooBar Alternately b/Print FooBar Alternately
new file mode 100644
index 0000000..af087fd
--- /dev/null
+++ b/Print FooBar Alternately	
@@ -0,0 +1,30 @@
+class FooBar {
+private:
+    int n;
+    mutex m1,m2;
+public:
+    FooBar(int n) {
+        m2.lock();
+        this->n = n;
+    }
+
+    void foo(function<void()> printFoo) {
+        
+        for (int i = 0; i < n; i++) {
+            m1.lock();
+        	// printFoo() outputs "foo". Do not change or remove this line.
+        	printFoo();
+            m2.unlock();
+        }
+    }
+
+    void bar(function<void()> printBar) {
+        
+        for (int i = 0; i < n; i++) {
+            m2.lock();
+        	// printBar() outputs "bar". Do not change or remove this line.
+        	printBar();
+            m1.unlock();
+        }
+    }
+};
diff --git a/Rank Scores b/Rank Scores
new file mode 100644
index 0000000..cc20088
--- /dev/null
+++ b/Rank Scores	
@@ -0,0 +1,19 @@
+import pandas as pd
+
+def order_scores(scores: pd.DataFrame) -> pd.DataFrame:
+    occr_dict = Counter(scores["score"])
+    
+    intr_arr = []
+    for key, freq in occr_dict.items():
+        intr_arr.append([key, freq])
+    
+    intr_arr.sort(reverse = True)
+
+    ans = []
+
+    for i, e in enumerate(intr_arr):
+
+        for j in range(e[1]):
+            ans.append([e[0], i + 1])
+    
+    return pd.DataFrame(ans, columns=["score", "rank"])