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Is there a way to have insertion of tags or labels with respect to a certain value range?

I have this data and would like to insert a new column titled 'Level'. I understand
'insert' is a mode of entering in a new column. I tried an 'if' for the argument 'value', but this is not yielding anything.
Data:
Active Discharged Deaths
State/UTs
Andaman and Nicobar 6 7437 129
Andhra Pradesh 14550 1993589 13925
Arunachal Pradesh 634 52507 267
Assam 6415 580491 5710
Bihar 55 716048 9656
Chandigarh 35 64273 814
Chhattisgarh 354 990757 13557
Dadra and Nagar Haveli and Daman and Diu 2 10659 4
Delhi 367 1412542 25082
Goa 885 170391 3210
Gujarat 152 815275 10082
Haryana 617 760271 9685
Himachal Pradesh 1699 209420 3613
Jammu and Kashmir 1286 320337 4410
Jharkhand 126 342716 5133
Karnataka 17412 2901299 37426
Kerala 239338 3966557 21631
Ladakh 54 20327 207
Lakshadweep 9 10288 51
Madhya Pradesh 125 781629 10516
Maharashtra 51234 6300755 137811
Manipur 3180 110602 1802
Meghalaya 2104 73711 1329
Mizoram 11414 54056 226
Nagaland 712 29045 631
Odisha 6322 997790 8055
Puducherry 914 121452 1818
Punjab 326 584079 16444
Rajasthan 86 945097 8954
Sikkim 913 28968 375
Tamil Nadu 16256 2572942 35036
Telengana 5505 650453 3886
Tripura 691 81866 803
Uttar Pradesh 227 1686369 22861
Uttarakhand 379 335358 7388
West Bengal 8480 1525581 18515
code:
data = Table.read_table('IndiaStatus.csv')#.drop('Discharged', 'Discharge Ratio (%)','Total Cases','Active','Deaths')
data2.info()
data3 = data2.set_index("State/UTs")
data3 = data3[["Active","Discharged","Deaths"]]
print(data3)
data3.insert(1, column = "Level", value = "Severe" if data3["Active"] > 91874)
output:
line 49
data3.insert(1, column = "Level", value = "Severe" if data3["Active"] > 91874)
^
SyntaxError: invalid syntax

The SyntaxError is because you need a else condition, so something like value = "Severe", if data3["Active"] > 91874 else 'OTHER' would remove the error. That said, it won't work in this case and return another error of using a Series - in this case data3["Active"] > 91874 - in a if statement.
I believe you can use np.where here
data3.insert(1, column = "Level",
value = np.where(data3["Active"] > 91874, "Severe", 'OTHER')
Replace OTHER in the above code by any value you want to assign in the column when the condition data3["Active"] > 91874 is not met

Print column with a specific value in python

I am using Colab.I am trying to print data form only NY,NC, SC State
confirmed_cases_USA, deaths_USA = get_confirmed_deaths_tuple_df (USA_covid_data)
# selecting rows based on condition PA, IL,OH,GA ,NC
options = ['NC',"PA"]
#options = ['NC',"PA","IL","OH","GA"]
confirmed_cases_Selected = confirmed_cases_USA[confirmed_cases_USA ['State'].isin(options)]
deaths_Selected= deaths_USA [deaths_USA ['State'].isin(options)]
print(confirmed_cases_Selected.head())
print(deaths_Selected.head())
output is :
countyFIPS County Name State ... 9/19/20 9/20/20
1921 0 Statewide Unallocated NC ... 1166 1166 1166
1922 37001 Alamance County NC ... 3695 3728 3749
1923 37003 Alexander County NC ... 483 485 488
1924 37005 Alleghany County NC ... 219 220 220
1925 37007 Anson County NC ... 549 552 553
countyFIPS County Name State ... 9/19/20 9/20/20
1921 0 Statewide Unallocated NC ... 0 0
1922 37001 Alamance County NC ... 48 54 54
1923 37003 Alexander County NC ... 5 5 5
1924 37005 Alleghany County NC ... 0 0 0
1925 37007 Anson County NC ... 4 4 4
I am trying to Group the data by state first and then get the total to confirm case of the state

I'm not sure what get_confirmed_deaths_tuple_df does but it doesn't look like a DataFrame.
USA_covid_data['State'].isin(options) should return a boolean mask containing True and False. Return the values that satisfy the True condition with USA_covid_data[USA_covid_data['State'].isin(options)]
It should look something like this.
confirmed_cases_USA, deaths_USA = get_confirmed_deaths_tuple_df(USA_covid_data[USA_covid_data['State'].isin(options)])

How to scrape tbody from a collapsible table using BeautifulSoup library?

Recently i did a project based of covid-19 dashboard. Where i use to scrape data from this website which has a collapsible table. Everything was ok till now, now recently the heroku app showing some errors. So i rerun my code in my local machine and the error occured at scraping tbody. Then i figured out that the site i use to scrape data has changed or updated the way it looks (table) and then my code is not able to grab it. I tried viewing page source and i am not able to find the table (tbody) that is on this page.But i am able to find tbody and all the data if i inspect the row of the table but cant find it on page source.How can i scrape the table now ?
My code:
The table i have to grab:

The data you see on the page is loaded from external URL via Ajax. You can use requests/json module to load it:
import json
import requests
url = 'https://www.mohfw.gov.in/data/datanew.json'
data = requests.get(url).json()
# uncomment to print all data:
# print(json.dumps(data, indent=4))
# print some data on screen:
for d in data:
print('{:<30} {:<10} {:<10} {:<10} {:<10}'.format(d['state_name'], d['active'], d['positive'], d['cured'], d['death']))
Prints:
Andaman and Nicobar Islands 329 548 214 5
Andhra Pradesh 75720 140933 63864 1349
Arunachal Pradesh 670 1591 918 3
Assam 9814 40269 30357 98
Bihar 17579 51233 33358 296
Chandigarh 369 1051 667 15
Chhattisgarh 2803 9086 6230 53
... and so on.

Try:
import json
import requests
import pandas as pd
data = []
row = []
r = requests.get('https://www.mohfw.gov.in/data/datanew.json')
j = json.loads(r.text)
for i in j:
for k in i:
row.append(i[k])
data.append(row)
row = []
columns = [i for i in j[0]]
df = pd.DataFrame(data, columns=columns)
df.sno = pd.to_numeric(df.sno, errors='coerce').reset_index()
df = df.sort_values('sno',)
print(df.to_string())
prints:
sno state_name active positive cured death new_active new_positive new_cured new_death state_code
0 0 Andaman and Nicobar Islands 329 548 214 5 403 636 226 7 35
1 1 Andhra Pradesh 75720 140933 63864 1349 72188 150209 76614 1407 28
2 2 Arunachal Pradesh 670 1591 918 3 701 1673 969 3 12
3 3 Assam 9814 40269 30357 98 10183 41726 31442 101 18
4 4 Bihar 17579 51233 33358 296 18937 54240 34994 309 10
5 5 Chandigarh 369 1051 667 15 378 1079 683 18 04
6 6 Chhattisgarh 2803 9086 6230 53 2720 9385 6610 55 22
7 7 Dadra and Nagar Haveli and Daman and Diu 412 1100 686 2 418 1145 725 2 26
8 8 Delhi 10705 135598 120930 3963 10596 136716 122131 3989 07
9 9 Goa 1657 5913 4211 45 1707 6193 4438 48 30
10 10 Gujarat 14090 61438 44907 2441 14300 62463 45699 2464 24
and so on...

Reshape data frame (with R or

I want to know if it's possible to have this result:
exemple:
With this data frame
df
y Faisceaux destination Trajet RED_Groupe Nbr observation RED Pond Nbr observation total RED pct
1 2015 France DOM-TOM Aller 78248.47 87 85586.75 307 0.9142591 0.04187815
2 2015 Hors Schengen Aller 256817.64 234 195561.26 1194 1.3132337 0.06015340
3 2015 INTERNATIONAL Aller 258534.78 473 288856.53 2065 0.8950283 0.04099727
4 2015 Maghreb Aller 605514.45 270 171718.14 1130 3.5262113 0.16152007
5 2015 NATIONAL Aller 361185.82 923 1082529.19 5541 0.3336500 0.01528302
6 2015 Schengen Aller 312271.06 940 505181.07 4190 0.6181369 0.02831411
7 2015 France DOM-TOM Retour 30408.70 23 29024.60 108 1.0476871 0.04798989
8 2015 Hors Schengen Retour 349805.15 225 168429.96 953 2.0768583 0.09513165
9 2015 INTERNATIONAL Retour 193536.63 138 99160.52 678 1.9517509 0.08940104
10 2015 Maghreb Retour 302863.83 110 41677.90 294 7.2667735 0.33285861
11 2015 NATIONAL Retour 471520.80 647 757258.33 3956 0.6226684 0.02852167
12 2015 Schengen Retour 307691.66 422 243204.76 2104 1.2651548 0.05795112
without using Exel.
With R or Python? I don't know if spliting column like that is possible.

thanks to all the comment here my solution :
I split my data frame into two data frame df15 ( with 2015 data) and df16 (2016 data) then :
mytable15 <- tabular(Heading()*Faisceaux_destination ~ Trajet*(`RED_Groupe` + `Nbr observation RED` + Pond + `Nbr observation total` + RED + pct)*Heading()*(identity),data=df15)
mytable16 <- tabular(Heading()*Faisceaux_destination ~ Trajet*(`RED_Groupe` + `Nbr observation RED` + Pond + `Nbr observation total` + RED + pct)*Heading()*(identity),data=df16)

Pandas data pull - messy strings to float

I am new to Pandas and I am just starting to take in the versatility of the package. While working with a small practice csv file, I pulled the following data in:
Rank Corporation Sector Headquarters Revenue (thousand PLN) Profit (thousand PLN) Employees
1.ÿ PKN Orlen SA oil and gas P?ock 79 037 121 2 396 447 4,445
2.ÿ Lotos Group SA oil and gas Gda?sk 29 258 539 584 878 5,168
3.ÿ PGE SA energy Warsaw 28 111 354 6 165 394 44,317
4.ÿ Jer¢nimo Martins retail Kostrzyn 25 285 407 N/A 36,419
5.ÿ PGNiG SA oil and gas Warsaw 23 003 534 1 711 787 33,071
6.ÿ Tauron Group SA energy Katowice 20 755 222 1 565 936 26,710
7.ÿ KGHM Polska Mied? SA mining Lubin 20 097 392 13 653 597 18,578
8.ÿ Metro Group Poland retail Warsaw 17 200 000 N/A 22,556
9.ÿ Fiat Auto Poland SA automotive Bielsko-Bia?a 16 513 651 83 919 5,303
10.ÿ Orange Polska telecommunications Warsaw 14 922 000 1 785 000 23,805
I have two serious problems with it that I cannot seem to find solution for:
1) data in "Ravenue" and "Profit" columns is pulled in as strings because of funny formatting with spaces between thousands, and I cannot seem to figure out how to make Pandas translate into floating point values.
2) Data under "Rank" column is pulled in as "1.?", "2.?" etc. What's happening there? Again, when I am trying to re-write this data with something more appropriate like "1.", "2." etc. the DataFrame just does not budge.
Ideas? Suggestions? I am also open for outright bashing because my problem might be quite obvious and silly - excuse my lack of experience then :)

I would use the converters parameter.
pass this to your pd.read_csv call
def space_float(x):
return float(x.replace(' ', ''))
converters = {
'Revenue (thousand PLN)': space_float,
'Profit (thousand PLN)': space_float,
'Rank': str.strip
}
pd.read_csv(... converters=converters ...)