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this is a part of my dataset:
img
I would like to sum the 2 rows that present "Trentino Alto Adige" both in order to have one single row, preserving the "Date" column.
I tried to do this using the groupby and sum functions but it does not work.
This is my attempt:
df = df.groupby(["Date"],["Region"]).sum()
The output is:
TypeError: unhashable type: 'list'
How should I rewrite my code? Thank you
Your groupby is not properly written, it should be:
df = df.groupby(["Date", "Region"]).sum()
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I have a dataset with a column containing strings in multiple languages. I am hoping to remove rows where one column contains a string in any language other than English. I can't seem to find any way to go about this. Does anyone have suggestions for a library or code that might be useful for this purpose?
This seems like a repeat of this, as the root of this question is how to detect non-English languages rather than how to filter a dataset.
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I'm trying to compare frames of a video and to find out the similarity of the frames.
The result should be something like a percentage
Do you have any idea guys?
Thanks
I would use ffmpeg-python to extract both videos as an image sequence and get general video stats, then use Pillow to compare each pixel for each frame individually.
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I have a text file that's content is like bellow(I think it's a JSON object):
{"t":[1322352000,1322438400] , "o":[123,123], "h":[123,123], "l":[123,123], "c":[123,123]}
The problem is, I don't know the number of elements in each array, but they are equal as they are stock data. I like to make a .csv file that each array will fill one column of it. But have no idea and experience to doing that!
How may I approach this?
You can use pandas data frame to convert your file:
import pandas as pd
#df = pd.read_json('/path/to/infile.json')
df = pd.DataFrame({"t":[1322352000,1322438400] , "o":[123,123], "h":[123,123], "l":[123,123], "c":[123,123]})
df.to_csv('/path/to/outfile.csv', sep=",")
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There are others but this example will get the point across
https://www.hackerrank.com/challenges/collections-counter/problem
The constraints say: 20 < price < 100 and 2 < shoe_size < 20 which means price does not include 20 or 100 and shoe_size does not include 2 or 20 ... so why in their testing data do they require that you include this invalid data for you to get the "correct" answer?
Note: The data which includes this is in a data_set, answer pair I bought to try and figure out why I was not passing all of the tests.
Answer provided via IRC at bhansa's suggestion. The guy/gal that answered wasn't associated with hackerrank but (s)he suggested to report it as an issue and this was not supposed to be a normal behavior regardless of how frequently I have seen it pop up.
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Is there a way we can read the alphabets from an image, some kind of text recognition method using python.
What I have to do is, read some images to get the text written on them.
Please suggest.
See OCROPUS
EDIT:
Also after seeing the other question here (of which this question is a duplicate), pytesser is much simpler if your image only contains text and no noise (images/illustrations)