How to divide hours in 15m intervals and distribute the values ​of each hour in python?

问题

| Month     | day | hour | Temperature |
|-----------|-----|------|-------------|
| September | 01  | 0:00 | 19,11       |
| September | 01  | 1:00 | 18,67       |
| September | 01  | 2:00 | 18,22       |
| September | 01  | 3:00 | 17,77       |


convert to:

| Month     | day | hour | Temperature |
|-----------|-----|------|-------------|
| September | 01  | 0:00 | T = 19,11       |
| September | 01  | 0:15 | T2 = T + (18,67 - 19,11)/ 4 |
| September | 01  | 0:30 | T3 = T2 + (18,67 - 19,11)/4  |
| September | 01  | 0:45 | T4 = T3 + (18,67 - 19,11)/4 |
| September | 01  | 1:00 | T = 18,67                       |
| September | 01  | 1:15 | T2 = T + (18,22 - 18,67)/ 4 |
| September | 01  | 1:30 | T3 = T2 + (18,22 - 18,67)/4  |
| September | 01  | 1:45 | T4 = T3 + (18,22 - 18,67)/4 |
| September | 01  | 2:00 | T = 18,22       |

. . .

I have this in an excel file and wanted to make these changes in python. Initially I upload the dataset to a dataframe. Someone can help me?

回答1:

I will give you a sample code:

x = df.Temperature.str.split(",", expand=True)

---

x:

    0   1
0   19  11
1   18  67
2   18  22
3   17  77

---

y = x[0].astype(int).diff().div(4).fillna(x.iloc[0,0]).astype(float).cumsum()

y:

0    19.00
1    18.75
2    18.75
3    18.50
Name: 0, dtype: float64

Do it for other column as well and then merge them together to get "<num1>, <num2>"

1st stage: resample:

df[['temp1', 'temp2']] = df.Temperature.str.split(",", expand=True)
df['temp1'] = df['temp1'].astype(int)
df['temp2'] = df['temp2'].astype(int)

u = pd.to_datetime(df['hour'], format='%H:%M')#.dt.hour
df['hr'] = u.dt.hour
df = df.set_index(u)
df1 = df.resample('900s').pad()

---

df1:

2nd Stage

<to be continued>

Edit2:

df['hour'] = pd.to_datetime(df['hour'], format='%H:%M')
df.set_index('hour', inplace=True)
v = df.resample('15T').bfill().reset_index()

v[['temp1', 'temp2']] = v.Temperature.str.split(",", expand=True)
v['temp1'] = v['temp1'].astype(int)
v['temp2'] = v['temp2'].astype(int)

t = v.groupby(v['hour'].dt.hour)
    
def calc(val1, val2):
    diff1 = (val1['temp1']-val2['temp1'])
    diff1.iloc[0]= val1['temp1'].iloc[0]*4
    
    diff2 = (val1['temp2']-val2['temp2'])
    diff2.iloc[0]= val1['temp2'].iloc[0]*4
    
    t1_group = diff1.div(4).cumsum()
    t2_group = diff2.div(4).cumsum()
    
    return list(zip(t1_group, t2_group))

concat_res = []
for _, gr in t:
     concat_res.append(calc(gr, gr.iloc[0]))

flatten = lambda t: [item for sublist in t for item in sublist]
v['Temperature'] = flatten(concat_res)
v = v.drop(['temp1', 'temp2'],axis=1)

---

v:

来源：https://stackoverflow.com/questions/65395578/how-to-divide-hours-in-15m-intervals-and-distribute-the-values-of-each-hour-in