How to extract specific rows using Python?

Question

My sample dataset. My original dataset contains 40,000 rows and 4 columns.

I want to extract rows where all sentiment columns are the same (either all positive like Document 2, 5, and 6 or all negative like Document 3).

How can I do this by using python?

Thank you for your suggestions and advice.

I made some correction. I used this: negative_df = df[df['Sentiment_B']<0]. But this only extract on the basis of Sentiment_B column. I want something which extract rows where Sentiment_A, Sentiment_B and Sentiment_C all are negative or positive. — Piyush Ghasiya
– Piyush Ghasiya, Commented Oct 23, 2020 at 9:37

Sivaram Rasathurai · Accepted Answer · 2020-10-23 04:17:48Z

1

Based on column condition

Thanks, David for pointing out the type changing.

df['Sentiment_B'] = pd.to_numeric(df['Sentiment_B'], errors='coerce')
positive_df = df[df['sentiment_B'>0]] 
nagative_df = df[df['sentiment_B'<0]]

answered Oct 23, 2020 at 3:07

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2 Comments

I got the error: TypeError: '<' not supported between instances of 'str' and 'int'.

try this first: df['Sentiment_B'] = pd.to_numeric(df['Sentiment_B'], errors='coerce')