Please help me
The below one is the problem...
write an expression to extract a new dataframe containing those days where the temperature reached at least 70 degrees, and assign that to the variable at_least_70. (You might need to think some about what the different columns in the full dataframe represent to decide how to extract the subset of interest.) After that, write another expression that computes how many days reached at least 70 degrees, and assign that to the variable num_at_least_70.
This is the original DataFrame
Date Maximum Temperature Minimum Temperature \
0 2018-01-01 5 0
1 2018-01-02 13 1
2 2018-01-03 19 -2
3 2018-01-04 22 1
4 2018-01-05 18 -2
.. ... ... ...
360 2018-12-27 33 23
361 2018-12-28 40 21
362 2018-12-29 50 37
363 2018-12-30 37 24
364 2018-12-31 35 25
Average Temperature Precipitation Snowfall Snow Depth
0 2.5 0.04 1.0 3.0
1 7.0 0.03 0.6 4.0
2 8.5 0.00 0.0 4.0
3 11.5 0.00 0.0 3.0
4 8.0 0.09 1.2 4.0
.. ... ... ... ...
360 28.0 0.00 0.0 1.0
361 30.5 0.07 0.0 0.0
362 43.5 0.04 0.0 0.0
363 30.5 0.02 0.7 1.0
364 30.0 0.00 0.0 0.0
[365 rows x 7 columns]
I wrote the code for the above problem is`
at_least_70 = dfc.loc[dfc['Minimum Temperature']>=70,['Date']]
print(at_least_70)
num_at_least_70 = at_least_70.count()
print(num_at_least_70)
The Results it is showing
Date
204 2018-07-24
240 2018-08-29
245 2018-09-03
Date 3
dtype: int64
But when run the test case it is showing... Incorrect! You are not correctly extracting the subset.
CodePudding user response：
As suggested by @HenryYik, remove the column selector:
at_least_70 = dfc.loc[dfc['Minimum Temperature'] >= 70]
num_at_least_70 = len(at_least_70)
CodePudding user response：
Use boolean indexing and for count Trues of mask use sum:
mask = dfc['Minimum Temperature'] >= 70
at_least_70 = dfs[mask]
num_at_least_70 = mask.sum()