将行插入特定索引到 Dataframe

Question

I want to insert specific rows to a dataframe. The dataframe contains id, hourname and count columns. I want to insert rows to the hours (0-23) which has no data. This is my dataframe,

      index  id                          hourname  count
           0  a                               0         1
           1  a                               4         1
           2  a                               14        1
           3  a                               15        3
           4  a                               17        1
           5  a                               20        1

and this is what I want to achieve

      index  id                          hourname  count
           0  a                               0         1
           1  a                               1         0
           2  a                               2         0
           3  a                               3         0
           4  a                               4         1
           5  a                               5         0
           6  a                               6         0 
           7  a                               7         0
           8  a                               8         0
           9  a                               9         0
           10 a                               10        0
           11 a                               11        0
           12 a                               12        0
           13 a                               13        0
           14 a                               14        1
           15 a                               15        3
           16 a                               16        0
           17 a                               17        1
           18 a                               18        0
           19 a                               19        0
           20 a                               20        1
           21 a                               21        0
           22 a                               22        0
           23 a                               23        0

I grab data from a csv file, here is the file content (name of file is a.csv in source code)

,id,hourname,count
0,a,0,1
1,a,4,1
2,a,14,1
3,a,15,3
4,a,17,1
5,a,20,1

and here is my source code

import csv
import pandas as pd
import numpy as np

result4 = pd.read_csv("a.csv")
print(result4)
for i in range(0,23):
    if result4.loc[i, 'hourname'] != i:
        line = pd.DataFrame({"id": "a", "hourname": i, "count":0}, index=[i])
        result4 = result4.append(line, ignore_index=False)
    result4 = result4.sort_index().reset_index(drop=True)
print(result4)

Answer 1

I hope this answers your question?

import pandas as pd
x = [0, 4, 14, 15, 17, 20]
y = [1, 1, 1, 3, 1, 1]
k = list(range(0,24))
i = list(set(k) - set(x))
for itm in i:
    x.insert(itm,itm)
    y.insert(itm, 0)
data = {'id': len(x) * ['a'], 'hourname': x, 'count': y}
df = pd.DataFrame(data) 
print(df)

I simply created a list k that contains integers from 0 to 23, then I got the difference between list x and list k as list i . After these, I iterated through list i adding it's items to list x and 0s at adjacent indicies in list y

Answer 2

Try,

hours_df = pd.DataFrame({'hourname': range(0,23)})
df = your_df.merge(hours_df, how='right', on='hourname')

This will give you all the hours. Then to fill the missing id and count

df['id'] = df['id'].ffill()
df['count'] = df['count'].fillna(0)