在Python中从pandas DataFrame提取数据

Question

This is a sample of the DataFrame that I have and I want to extract the corresponding data of "totalCount" according to each time frame.

df = [{"username": "last",
"time_data": "{\"hours\":[{\"hour\":\"00:00\",\"postCount\":\"5\",\"topicCount\":\"3\",\"totalCount\":80},{\"hour\":\"01:00\",\"postCount\":\"11\",\"topicCount\":\"6\",\"topciCount\":31}"
},
{"username": "truk",
 "time_data": "{\"hours\":[{\"hour\":\"00:00\",\"postCount\":\"11\",\"topicCount\":\"6\",\"totalCount\":362},{\"hour\":\"01:00\",\"postCount\":\"22\",\"topicCount\":\"8\",\"topicCount\":355}"
}]
df = pd.DataFrame(df)
df

I have used this code to get the "postCount" of both '00:00' and '01:00':

df_h0 = df.copy()
df_h0['hour']='00:00'
df_h0['totalCount']=df.time_data.str.split('"00:00","postCount":"').str[1].str.split('","topic').str[0]
df_h0 = df_h0.fillna(0)

df_h1 = df.copy()
df_h1['hour']='01:00'
df_h1['totalCount']=df.time_data.str.split('"01:00","postCount":"').str[1].str.split('","topic').str[0]
df_h1 = df_h1.fillna(0)

df_tot = df_h0.append([df_h1])
df_tot.head()

But now I want to get the "totalCount" which is not just next to the hours. Anyone knows how to do that?

Expected output:

                           time_data                 username   hour    totalCount
0   {"hours":[{"hour":"00:00","postCount":"5","top...   last    00:00   80
1   {"hours":[{"hour":"00:00","postCount":"11","to...   truk    00:00   362
0   {"hours":[{"hour":"00:00","postCount":"5","top...   last    01:00   31
1   {"hours":[{"hour":"00:00","postCount":"11","to...   truk    01:00   355

Answer 1

To solve the problem as it stands you should make a regular expression to extract the text at the correct position. But this is not the correct way to approach your problem. Ideally, to make the most of the DataFrame structure, you should parse the data when it is received into DataFrame colums so that you could use something more convenient and efficient:

totals_over_one_hundred = df.loc[df['totalCount'] > 100]