<pre class="lang-python prettyprint-override"><code>
In [2]: df = pd.DataFrame({'num': {0: 3234, 1: 3433, 2: 4443},
...: 'URL': {0: 'http://example.com/images/41456gn7L.jpg',
...: 1: 'http://example.com/images/31mndfg.jpg',
...: 2: 'http://example.com/images/dsfsdf8587eh.jpg'},
...: 'meta_data': {0: "[{'id': 0, 'imageUrl': 'http://example.com/images/41dY3ASVn7L.jpg' 'score': 54.09280014038086}, {'id': 0, 'imageUrl': 'http://examp
...: le.com/images/41dY3ASVn7L.jpg', 'score': 54.09280014038086}]",
...: 1: "[{'id': 0, 'imageUrl': 'http://example.com/images/31mnLrB5IHL.jpg' 'score': 99.902099609375}, {'id': 0, 'imageUrl': 'http://example.com/images/3
...: 1mnLrB5IHL.jpg', 'score': 99.902099609375}]",
...: 2: "[{'id': 0, 'imageUrl': 'http://example.com/images/4189TDx0e0L.jpg' 'score': 97.33160400390625}, {'id': 0, 'imageUrl': 'http://example.com/images
...: /4189TDx0e0L.jpg', 'score': 97.33160400390625}]"}})
...: file_names = ["41456gn7L.jpg","31mndfg.jpg","dsfsdf8587eh.jpg"]
...: df
Out[2]:
num URL meta_data
0 3234 http://example.com/images/41456gn7L.jpg [{'id': 0, 'imageUrl': 'http://example.com/ima...
1 3433 http://example.com/images/31mndfg.jpg [{'id': 0, 'imageUrl': 'http://example.com/ima...
2 4443 http://example.com/images/dsfsdf8587eh.jpg [{'id': 0, 'imageUrl': 'http://example.com/ima...
In [3]: df['Score'] = df.loc[df.URL.apply(lambda x:x.split("/")[-1]).isin(file_names), :].meta_data.apply(lambda x:x.split(",")[-1]).str.extract(r"([\d]*[.][\
...: d]+)")
In [4]: df
Out[4]:
num URL meta_data Score
0 3234 http://example.com/images/41456gn7L.jpg [{'id': 0, 'imageUrl': 'http://example.com/ima... 54.09280014038086
1 3433 http://example.com/images/31mndfg.jpg [{'id': 0, 'imageUrl': 'http://example.com/ima... 99.902099609375
2 4443 http://example.com/images/dsfsdf8587eh.jpg [{'id': 0, 'imageUrl': 'http://example.com/ima... 97.33160400390625
</code></pre>