Python 循环：类型错误：字符串索引必须是整数

Question

For a current research project, I am planning to read the JSON object "Main_Text" within a pre-defined time range on basis of Python/Pandas. When running the word-counting loop, the code however yields the error TypeError: string indices must be integers for line = row['Text Main'] .

Text Main only contains strings/text and no integers. I have alreay been through trouble-shooting threads but not found a solution to this problem yet. Is there any helpful tweak to make this work?

The JSON file has the following structure:

[
{"No":"121","Stock Symbol":"A","Date":"05/11/2017","Text Main":"Sample text"}
]

And the relevant code excerpt looks like this:

import string
import json
import csv

import pandas as pd
import datetime

import numpy as np


# Loading and reading dataset
file = open("Glassdoor_A.json", "r")
data = json.load(file)
df = pd.json_normalize(data)
df['Date'] = pd.to_datetime(df['Date'])


# Create an empty dictionary
d = dict()


# Filtering by date
start_date = "01/01/2009"
end_date = "01/01/2015"

after_start_date = df["Date"] >= start_date
before_end_date = df["Date"] <= end_date

between_two_dates = after_start_date & before_end_date
filtered_dates = df.loc[between_two_dates]

print(filtered_dates)


# Processing
for row in filtered_dates:
    line = row['Text Main']

Answer 1

filtered_dates will return an iterator on the column names which are strings. If you want to iterate over the rows you should use iterrows().

Something like that should work:

import string
import json
import csv

import pandas as pd
import datetime

import numpy as np


# Loading and reading dataset
file = open("Glassdoor_A.json", "r")
data = json.load(file)
df = pd.json_normalize(data)
df['Date'] = pd.to_datetime(df['Date'])


# Create an empty dictionary
d = dict()


# Filtering by date
start_date = "01/01/2009"
end_date = "01/01/2015"

after_start_date = df["Date"] >= start_date
before_end_date = df["Date"] <= end_date

between_two_dates = after_start_date & before_end_date
filtered_dates = df.loc[between_two_dates]

# Processing
for index, row in filtered_dates.iterrows():
    line = row['Text Main']