将熊猫中来自不同df的不同列合并为一个df时出错

Question

I have two CSV files(attached screenshots). One with Datetime column and one without Datetime column. I want to join these both dfs into one df(attached screenshot). So I tried

main_data = pd.concat([Group_avg, weather_avg], axis=1, join='inner')
main_data.columns = ['Avg Current(mA)', 'Avg T-in(degC)', 'T-out(degC)', 'RH-out(%)']

And when I printed main_data, there were only column names present without any data(as shown in screenshot).

Desired output

CSV 1

CSV 2 Error

Answer 1

Assuming rows in each file correspond to each other you can merge on the index:

main_data = pd.merge(Group_avg, weather_avg, left_index=True, right_index=True)

You can also specify different merge types (eg left, right, innner, outer). See here for documentation.

If the indexes don't correspond in the files then you will need a way of matching up the rows from each file when merging as currently it doesn't look like there's any obvious column to merge on in both files.

Also, when reading in the CSV files, remove the index_col = 0 parameter, as this is telling pandas to use the first column in each file as the row index, which doesn't look right.