Shulou(Shulou.com)06/02 Report--

This article is about how to use pandas to merge irregular data in Python, the editor thinks it is very practical, so I share it with you to learn. I hope you can get something after reading this article.

A method for resetting the header is defined here:

-x_df.head (10) .isin (cols) .sum (axis=1) > = 2. Use the first 10 rows of data in the table and use the specified header to find it. As long as a row has content greater than or equal to 2 matches, this row is used as the title.

-x_df.columns = x _ df.loc. header _ idx]. You can easily set its header through DataFrame.columns

-xdf.iloc [header _ idx+1:] .loc [:, cols], .iloc [header _ idx+1:]: get the data after the header. .loc [:, cols]: get the specified column

There are many kinds of pandas knowledge involved here. I hope you can learn them systematically. I can only recommend you to take a look at my pandas column.

Let's see how to call:

-the code here is basically the same as the previous section in this series

-when using pd.read_excel to load data, set header=None (red line) so that it does not set any data as the header

-after loading the data, call the previously defined method reset_header to adjust the table (green line)

The above is how to use pandas to merge irregular data in Python. The editor believes that there are some knowledge points that we may see or use in our daily work. I hope you can learn more from this article. For more details, please follow the industry information channel.

Welcome to subscribe "Shulou Technology Information " to get latest news, interesting things and hot topics in the IT industry, and controls the hottest and latest Internet news, technology news and IT industry trends.