OOF simply stands for “Out-of-fold” and refers to a step in the learning process when using k-fold validation in which the predictions from each set of folds are grouped together into one group of 1000 predictions. These predictions are now “out-of-the-folds” and thus error can be calculated on these to get a good measure of … Read more
According to kaggle api documentation the location where credentials json is looking for is ~/.kaggle/kaggle.json as google colab environment is Linux based. In your snippet you try to config path parameter, but it is not used to looking for credential json: – path: Folder where file(s) will be downloaded, defaults to current working directory So … Read more
It’s still most likely gzipped data. gzip’s magic number is 0x1f 0x8b, which is consistent with the UnicodeDecodeError you get. You could try decompressing the data on the fly: with open(‘destinations.csv’, ‘rb’) as fd: gzip_fd = gzip.GzipFile(fileobj=fd) destinations = pd.read_csv(gzip_fd) Or use pandas’ built-in gzip support: destinations = pd.read_csv(‘destinations.csv’, compression=’gzip’)
If you like %magic, you can also use %env to make it a bit shorter. %env KAGGLE_USERNAME=abcdefgh If the value is in a variable you can also use %env KAGGLE_USERNAME=$username
Step-by-step — Create an API key in Kaggle. To do this, go to kaggle.com/ and open your user settings page. Next, scroll down to the API access section and click generate to download an API key. This will download a file called kaggle.json to your computer. You’ll use this file in Colab to access Kaggle … Read more
If you only need to get list of unique values, you can just use unique method. If you want to have Python’s set, then do set(some_series) In [1]: s = pd.Series([1, 2, 3, 1, 1, 4]) In [2]: s.unique() Out[2]: array([1, 2, 3, 4]) In [3]: set(s) Out[3]: {1, 2, 3, 4} However, if you … Read more