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byte indices must be integers or slices, not str

I'm trying to run the below code
import requests
import pandas as pd
companies = requests.get(f'https://fmpcloud.io/api/v3/stock-screener? industry=Software&sector=tech&marketCapLowerThan=10000000000&limit=100&apikey=c609af2465eb19e3c82f0c3c38cb51ea')
companies.json()
At this point it's working fine but when getting to the following part , I was receiving an error
technological_companies = []
for item in companies:
technological_companies.append(item['symbol'])
print(technological_companies)
The error was :
Traceback (most recent call last)
<ipython-input-8-61eef8b7699a> in <module>
1 technological_companies = []
2 for item in companies:
----> 3 technological_companies.append(item['symbol'])
4 print(technological_companies)
TypeError: byte indices must be integers or slices, not str

You are not storing the JSON value, use
import requests
import pandas as pd
companies = requests.get(f'https://fmpcloud.io/api/v3/stock-screener? industry=Software&sector=tech&marketCapLowerThan=10000000000&limit=100&apikey=c609af2465eb19e3c82f0c3c38cb51ea')
companies = companies.json() # this is the line

Either store the json:
companies = companies.json()
Or loop over the json:
for item in companies.json():

TypeError: expected string or bytes-like object in Pandas

I want to tokenize text, but couldn't. How can I solve this?
Here is my problem:
#read_text from file
data = pd.read_csv("input data.txt",encoding = "UTF-8")
print(data)
Output: Bangla text
t = Tokenizers()
print(t.bn_word_tokenizer(data))
Error
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-17-f9f299ecf33d> in <module>
1 `t = Tokenizers()`
----> 2 `print(t.bn_word_tokenizer(dataStr))`
D:\anaconda\lib\site-packages\bnltk\tokenize\bn_word_tokenizers.py in bn_word_tokenizer(self, input_)
15 `tokenize_list` = []
16 `r = re.compile(r'[\s\।{}]+'.format(re.escape(punctuation)))`
---> 17 `list_ = r.split(input_)`
18 `list_ = [i for i in list_ if i`]
19 `return list_`
TypeError: expected string or bytes-like object

Try this:
for column in data:
a = data.apply(lambda row: t.bn_word_tokenizer(row), axis=1)
print(a)
This will print one column at a time. If you want to convert the entire dataframe rather than just print then replace a with data[column] in the code above.

'module' object is not callable error in jupyter notebook

Initially, I was getting "list object is not callable" error but after "importing list " new error came in the picture as shown below.
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
imort list
data_cols=['user id','movie id','rating','timestamp']
item_cols=['movie id','movie title','release date','video release date','IMDb URL','unknown','Action','Adventure','Animation','Childrens','Comedy','Crime','Documentary','Drama','Fantasy','Film-Noir','Horror','Musical','Mystery','Romance ','Sci-Fi','Thriller','War' ,'Western']
user_cols = ['user id','age','gender','occupation','zip code']
#importing the data files onto dataframes
users=pd.read_csv('u.user',sep='|',names=user_cols,encoding='latin-1')
item=pd.read_csv('u.item',sep='|',names=item_cols,encoding='latin-1')
data=pd.read_csv('u.data',sep='\t',names=data_cols,encoding='latin-1')
dataset=pd.merge(pd.merge(item,data),users)
#print(dataset.head())
rating_total=dataset.groupby('movie title').size()
rating_mean=(dataset.groupby('movie title'))['movie title','rating']
rating_mean=rating_mean.mean()
rating_total=pd.DataFrame({'movie title':rating_total.index,'total
ratings':rating_total.values})
rating_mean['movie title']=rating_mean.index
final=pd.merge(rating_mean,rating_total).sort_values(by='total
ratings',ascending=False)
pop=final[:300].sort_values(by='rating',ascending=False)
pop=pop['movie title']
pop1=list(pop.head(10))
Output
TypeError Traceback (most recent call last)
<ipython-input-57-0b36af3a9876> in <module>
30 pop=pop['movie title']
31 #print(pop.head())
---> 32 pop1=list(pop.head(10))
TypeError: 'module' object is not callable

How to remove every possible accents from a column in python

I am new in python. I have a data frame with a column, named 'Name'. The column contains different type of accents. I am trying to remove those accents. For example, rubén => ruben, zuñiga=zuniga, etc. I wrote following code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import re
import unicodedata
data=pd.read_csv('transactions.csv')
data.head()
nm=data['Name']
normal = unicodedata.normalize('NFKD', nm).encode('ASCII', 'ignore')
I am getting error:
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-41-1410866bc2c5> in <module>()
1 nm=data['Name']
----> 2 normal = unicodedata.normalize('NFKD', nm).encode('ASCII', 'ignore')
TypeError: normalize() argument 2 must be unicode, not Series

The reason why it is giving you that error is because normalize requires a string for the second parameter, not a list of strings. I found an example of this online:
unicodedata.normalize('NFKD', u"Durrës Åland Islands").encode('ascii','ignore')
'Durres Aland Islands'

Try this for one column:
nm = nm.str.normalize('NFKD').str.encode('ascii', errors='ignore').str.decode('utf-8')
Try this for multiple columns:
obj_cols = data.select_dtypes(include=['O']).columns
data.loc[obj_cols] = data.loc[obj_cols].apply(lambda x: x.str.normalize('NFKD').str.encode('ascii', errors='ignore').str.decode('utf-8'))

Try this for one column:
df[column_name] = df[column_name].apply(lambda x: unicodedata.normalize(u'NFKD', str(x)).encode('ascii', 'ignore').decode('utf-8'))
Change the column name according to your data columns.

Getting error while trying to use a list with numpy to get some stat values

Hi I am having problems with this code:
**import numpy as np
# Summarize the data about minutes spent in the classroom
#total_minutes = total_minutes_by_account.values()
total_minutes = list(total_minutes_by_account.values())
type(total_minutes)
# Printing out the samething converting to a list
print('Printing out the samething converting to a list ')
print(type(total_minutes))
print ('Mean:', np.mean(total_minutes))
print ('Standard deviation:', np.std(total_minutes))
print ('Minimum:', np.min(total_minutes))
print ('Maximum:', np.max(total_minutes))**
The error I get is:
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-93-945375bf6098> in <module>()
3 # Summarize the data about minutes spent in the classroom
4 #total_minutes = total_minutes_by_account.values()
----> 5 total_minutes = list(total_minutes_by_account.values())
6 type(total_minutes)
7 #print(total_minutes)
AttributeError: 'list' object has no attribute 'values'
I really would lie to know how I can make this work, I can do it with pandas converitng it to a numpy array and the getting values for the statistics I want with numpy