I cannot assign a variable with Python's falsy [closed] - python

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I'm stuck. I want to assign a variable asset to a CSV file, if the file is absent, a second file is sought.
I got this code but it seems not to work.
a = pd.read_csv('me.csv') or 'report_generator.csv'
print(a)


You could try something like this:
import pandas as pd
try:
df = pd.read_csv('one.csv')
except:
df = pd.read_csv('two.csv')
print(df.head())
It would try to open 'one.csv', and if any error occurs (note that the error could be even if the csv exists but the data was corrupted), then it would open 'two.csv'.
[EDITED]
A more beautiful and safe solution would be checking whether the file exists explicitly:
import os.path as path
if path.exists('one.csv'):
df = pd.read_csv('one.csv')
elif path.exists('two.csv'):
df = pd.read_csv('two.csv')
else:
print("Could not find csv")

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How to get a specific string from file? [closed]

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I have a JSON file like this:
{"objects":[{"featureId":"ckm39acfw00043b6a4i8vv8zf","schemaId":"ckm399dnn07ax0y8hdncv51yy","title":"Buildings","value":"buildings","color":"#1CE6FF","bbox":{
top":110,"left":799,"height":42,"width":53},"instanceURI":<"https://api.labelbox.com/masks/feature/ckm39acfw00043b6a4i8vv8zf?token=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VySWQiOiJja20yN3F1aDVwNzh2MDc4OXh3YmE3eWo5Iiwib3JnYW5pemF0aW9uSWQiOiJja20yN3F0cm1wNzhvMDc4OXBlaHJiZG4wIiwiaWF0IjoxNjE1MzcyNjUxLCJleHAiOjE2MTc5NjQ2NTF9.ALYeG0mpNvnOpAuj6O3h0OFcrREOtOvJqqVqqt8xcqw"
},{"featureId":"ckm39agzr00073b6alzzwpm77","schemaId":"ckm399dnn07ax0y8hdncv51yy","title":"Buildings","value":"buildings","color":"#1CE6FF","bbox":
{"top":151,"left":875,"height":45,"width":120},"instanceURI":"https://api.labelbox.com/masks/feature/ckm39agzr00073b6alzzwpm77?token=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VySWQiOiJja20yN3F1aDVwNzh2MDc4OXh3YmE3eWo5Iiwib3JnYW5pemF0aW9uSWQiOiJja20yN3F0cm1wNzhvMDc4OXBlaHJiZG4wIiwiaWF0IjoxNjE1MzcyNjUxLCJleHAiOjE2MTc5NjQ2NTF9.ALYeG0mpNvnOpAuj6O3h0OFcrREOtOvJqqVqqt8xcqw"},{"featureId":"ckm39an0e000a3b6ae7vc0bo8","schemaId":"ckm399dnn07ax0y8hdncv51yy","title":"Buildings","value":"buildings","color":"#1CE6FF","bbox":{"top":635,"left":952,"height":93,"width":84},"instanceURI":"https://api.labelbox.com/masks/feature/ckm39an0e000a3b6ae7vc0bo8?token=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VySWQiOiJja20yN3F1aDVwNzh2MDc4OXh3YmE3eWo5Iiwib3JnYW5pemF0aW9uSWQiOiJja20yN3F0cm1wNzhvMDc4OXBlaHJiZG4wIiwiaWF0IjoxNjE1MzcyNjUxLCJleHAiOjE2MTc5NjQ2NTF9.ALYeG0mpNvnOpAuj6O3h0OFcrREOtOvJqqVqqt8xcqw"},{"featureId":"ckm39bbki000g3b6au6s5s3se","schemaId":"ckm399dnn07ax0y8hdncv51yy","title":"Buildings","value":"buildings","color":"#1CE6FF","bbox":{"top":646,"left":764,"height":74,"width":93},"instanceURI":"https://api.labelbox.com/masks/feature/ckm39bbki000g3b6au6s5s3se?token=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VySWQiOiJja20yN3F1aDVwNzh2MDc4OXh3YmE3eWo5Iiwib3JnYW5pemF0aW9uSWQiOiJja20yN3F0cm1wNzhvMDc4OXBlaHJiZG4wIiwiaWF0IjoxNjE1MzcyNjUxLCJleHAiOjE2MTc5NjQ2NTF9.ALYeG0mpNvnOpAuj6O3h0OFcrREOtOvJqqVqqt8xcqw"
},{"featureId":"ckm39cgdi000p3b6aru669fzh","schemaId":"ckm399dnn07ax0y8hdncv51yy","title":"Buildings","value":"buildings","color":"#1CE6FF","bbox":
{"top":375,"left":916,"height":52,"width":80},"instanceURI":"https://api.labelbox.com/masks/feature/ckm39cgdi000p3b6aru669fzh?token=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VySWQiOiJja20yN3F1aDVwNzh2MDc4OXh3YmE3eWo5Iiwib3JnYW5pemF0aW9uSWQiOiJja20yN3F0cm1wNzhvMDc4OXBlaHJiZG4wIiwiaWF0IjoxNjE1MzcyNjUxLCJleHAiOjE2MTc5NjQ2NTF9.ALYeG0mpNvnOpAuj6O3h0OFcrREOtOvJqqVqqt8xcqw"
},{"featureId":"ckm39ckyi000s3b6armui3tn3","schemaId":"ckm399dnn07ax0y8hdncv51yy","title":"Buildings","value":"buildings","color":"#1CE6FF","bbox":{"top":420,"left":914,"height":72,"width":86},"instanceURI":"https://api.labelbox.com/masks/feature/ckm39ckyi000s3b6armui3tn3?token=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VySWQiOiJja20yN3F1aDVwNzh2MDc4OXh3YmE3eWo5Iiwib3JnYW5pemF0aW9uSWQiOiJja20yN3F0cm1wNzhvMDc4OXBlaHJiZG4wIiwiaWF0IjoxNjE1MzcyNjUxLCJleHAiOjE2MTc5NjQ2NTF9.ALYeG0mpNvnOpAuj6O3h0OFcrREOtOvJqqVqqt8xcqw"
},{"featureId":"ckm39cp6a000v3b6a6cjj16xp","schemaId":"ckm399dnn07ax0y8hdncv51yy","title":"Buildings","value":"buildings","color":"#1CE6FF","bbox":{"top":478,"left":867,"height":66,"width":137},"instanceURI":"https://api.labelbox.com/masks/feature/ckm39cp6a000v3b6a6cjj16xp?token=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VySWQiOiJja20yN3F1aDVwNzh2MDc4OXh3YmE3eWo5Iiwib3JnYW5pemF0aW9uSWQiOiJja20yN3F0cm1wNzhvMDc4OXBlaHJiZG4wIiwiaWF0IjoxNjE1MzcyNjUxLCJleHAiOjE2MTc5NjQ2NTF9.ALYeG0mpNvnOpAuj6O3h0OFcrREOtOvJqqVqqt8xcqw"},{"featureId":"ckm39cyom000y3b6aqp2x5i0s","schemaId":"ckm399dnn07ax0y8hdncv51yy","title":"Buildings","value":"buildings","color":"#1CE6FF","bbox":{"top":703,"left":806,"height":85,"width":95},"instanceURI":"https://api.labelbox.com/masks/feature/ckm39cyom000y3b6aqp2x5i0s?token=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VySWQiOiJja20yN3F1aDVwNzh2MDc4OXh3YmE3eWo5Iiwib3JnYW5pemF0aW9uSWQiOiJja20yN3F0cm1wNzhvMDc4OXBlaHJiZG4wIiwiaWF0IjoxNjE1MzcyNjUxLCJleHAiOjE2MTc5NjQ2NTF9.ALYeG0mpNvnOpAuj6O3h0OFcrREOtOvJqqVqqt8xcqw"},{"featureId":"ckm39dz3t00143b6a2brbj4qi","schemaId":"ckm399dnn07ax0y8hdncv51yy","title":"Buildings","value":"buildings","color":"#1CE6FF","bbox":{"top":41,"left":823,"height":50,"width":80},"instanceURI":"https://api.labelbox.com/masks/feature/ckm39dz3t00143b6a2brbj4qi?token=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VySWQiOiJja20yN3F1aDVwNzh2MDc4OXh3YmE3eWo5Iiwib3JnYW5pemF0aW9uSWQiOiJja20yN3F0cm1wNzhvMDc4OXBlaHJiZG4wIiwiaWF0IjoxNjE1MzcyNjUxLCJleHAiOjE2MTc5NjQ2NTF9.ALYeG0mpNvnOpAuj6O3h0OFcrREOtOvJqqVqqt8xcqw"},{"featureId":"ckm39eco400173b6a35p84q7y","schemaId":"ckm399dnn07ax0y8hdncv51yy","title":"Buildings","value":"buildings","color":"#1CE6FF","bbox":{"top":31,"left":892,"height":62,"width":95},"instanceURI":"https://api.labelbox.com/masks/feature/ckm39eco400173b6a35p84q7y?token=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VySWQiOiJja20yN3F1aDVwNzh2MDc4OXh3YmE3eWo5Iiwib3JnYW5pemF0aW9uSWQiOiJja20yN3F0cm1wNzhvMDc4OXBlaHJiZG4wIiwiaWF0IjoxNjE1MzcyNjUxLCJleHAiOjE2MTc5NjQ2NTF9.ALYeG0mpNvnOpAuj6O3h0OFcrREOtOvJqqVqqt8xcqw"}],"classifications":[]}
and I want to save in array all occurrences of top, left, right, height and width. How can I do that?

Firstly, the JSON file does not look valid. For my answer I'll assume a valid file like so:
#example.json
{
"top":151,
"left":875,
"height":45,
"width":120
}
Next you can use python's builtin library 'json' to load the json and extract information:
import json
with open('test.json', 'r') as fh:
d = json.load(fh)
print(d.get('top'))
Notice that first you load the json file's content into a dictionary and then you can access it's contents in the same way you would a dictionary using d.get('top') or d['top']

Interactive Dictionary, TypeError: 'dict' not callable? [closed]

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import json
data = json.load(open("files1\data.json"))
def definitioner(w):
return data(w)
word = input("Enter the word you are looking for: ")
print(definitioner(word))
I am doing a course on UDEMY and after trying it myself it didn't work so I even copied the code to see if it was my code, couldn't figure out what the issue was, any help would be appreciated. I am running Python 3.8
Thanks.

You are calling data(w) like it's a function, but data is a dictionary. Use data.get(w) instead:
def definitioner(w):
return data.get(w)
That also allows you to specify what you would like returned by default if the word is not present, by adding a second argument:
def definitioner(w):
return data.get(w, 'Word not found!')

How can I convert this matlab code to python? [closed]

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I have a Matlab code implementing a for loop which I have to convert it to python code:
for i = 1:numel(file_list)
filename = file_list(i).name;
File_list consists of 207 CSV files having 3036*190 items. this is how the following part of the code looks like:
for i = 1:numel(file_list)
filename = file_list(i).name;
SS= strcat(filename);
ActualRadarData = csvread(SS);
RadarData = real(ActualRadarData(:,20:end));
and this is what I attempted in doing so which is not correct:
for i in 1:len(file_list):
filename = os.path.basename('/path/file_list')
This method doesn't work out. how can it be done correctly?

Python starts indexes at zero, unlike MATLAB which starts indexing at 1, so you should keep that in mind. If you want to iterate through a list, you'd usually do for element in list, although you could iterate through indexes as well.
import os
for file in file_list:
filename = os.path.basename(file)
I would recommend looking into a guide for indexing and looping in Python, and then for CSV reading I recommend using Pandas.

Is there a way to get all keys that match a string in a json file's values and output them to a text file? [closed]

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I'm trying to get all keys' values that equal "url" ignoring nesting from a JSON file and then output them to a text file. How would I go about doing this?
I'm running Python 3.7 and cannot seem to find a solution.
r = requests.get('https://launchermeta.mojang.com/mc/game/version_manifest.json')
j = r.json()
The result expected from this would be a text file filled with links from this json file.
https://launchermeta.mojang.com/v1/packages/31fa028661857f2e3d3732d07a6d36ec21d6dbdc/a1.2.3_02.json
https://launchermeta.mojang.com/v1/packages/2dbccc4579a4481dc8d72a962d396de044648522/a1.2.3_01.json
https://launchermeta.mojang.com/v1/packages/48f077bf27e0a01a0bb2051e0ac17a96693cb730/a1.2.3.json
etc.

Using requests library
import requests
response = requests.get('https://launchermeta.mojang.com/mc/game/version_manifest.json').json()
url_list = []
for result in response['versions']:
url_list.append(result['url'])
print(url_list)

conversion on pandas queries python [closed]

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I want to read a .dat file and to extract lines which their timestamp==2000 and to save them on a file, here is my code and I get that error on converting query error screenshot
can someone help me ?

make sure your field is a datetime
ratings_df['timestamp'] = pd.to_datetime(ratings_df['timestamp'])
You can then pull year from it
ratings_df['timestamp'].dt.year

I found the answer def dateparse (time_in_secs):
return datetime.datetime.fromtimestamp(float(time_in_secs))
ratings_df = pd.read_table('~/ml-1m/ratings.dat', header=None, sep='::', names=['user_id', 'movie_id', 'rating', 'timestamp'],parse_dates=['timestamp'],date_parser=dateparse)
thank you for your help

You should use the pandas function to_datetime instead of the native datetime functionality.
ratings_df.loc[pd.to_datetime(ratings_df['Timestamp'], unit='s').year == 2000, colonnes]
The format of the timestamp is an important factor to get the right output.

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