Given the following table:
| ENO | SALARY |
|---|---|
| A101 | 4000 |
| B109 | NULL |
| C508 | 6000 |
| A305 | 2000 |
State the output of the following query:
SELECT COUNT(SALARY) FROM EMPLOYEE;
| List-I (Aggregate function) | List-II (Description) |
|---|---|
(A) count(marks) | (III) Count all non null values of marks column |
(B) count() | (I) Count all rows |
(C) avg(marks) | (II) Finding average of non null values of marks |
(D) sum(marks) | (IV) Finding sum of all marks |
Given the following code for histogram:
df.plot(kind='hist', edgecolor="Green", linewidth=2, linestyle='-', fill=False, hatch='o')
What is the role of fill=False?
| LIST I | LIST II |
|---|---|
| A. DataFrame.std() | IV. Standard Deviation |
| B. DataFrame.describe() | III. Descriptive statistical values |
| C. DataFrame.var() | I. Variance |
| D. DataFrame.mode() | II. Value that appears most |
| State | Avg Temp (°C) | Rainfall (in cm) | Humidity |
|---|---|---|---|
| Assam | 20 | 150 | 10.6 |
| Delhi | 30 | 70 | 7.5 |
| Kerala | 20 | 120 | 10.9 |
| Rajasthan | 35 | 50 | 5.6 |
| Telangana | 28 | 90 | 8.7 |