Merge two lists (non equal elements) in a csv using pandas-CodePudding

I have two lists whose no. of elements are not equal. I want to put these two lists in a csv whose heading is 'video' and 'image'. But as the elements of these 2 lists are not the same I got an error.

ValueError: All arrays must be of the same length

import pandas as pd
VID = ['00001', '05445', '987457', '15455'] 
IMG = ['00001', '05445', '987457'] 

df = pd.DataFrame(data={"video": VID, "image": IMG})
df.to_csv("./file.csv", sep=',',index=False)

CodePudding user response：

You can convert to Series first:

import pandas as pd
VID = ['00001', '05445', '987457', '15455'] 
IMG = ['00001', '05445', '987457'] 

df = pd.DataFrame(data={"video": pd.Series(VID), "image": pd.Series(IMG)})
df.to_csv("./file.csv", sep=',',index=False)

More generic approach if many items:

names = ['video', 'image']
vals = [VID, IMG]
df = pd.DataFrame(dict(zip(names, map(pd.Series, vals))))
df.to_csv("./file.csv", sep=',',index=False)

CodePudding user response：

Suggestion 1:

Using None to create an "empty value"/null value

import pandas as pd
VID = ['00001', '05445', '987457', '15455'] 
IMG = ['00001', '05445', '987457', None] 

df = pd.DataFrame(data={"video": VID, "image": IMG})

Suggestion 2:

import pandas as pd
VID = ['00001', '05445', '987457', '15455'] 
IMG = ['00001', '05445', '987457', '0'] 

df = pd.DataFrame(data={"video": VID, "image": IMG})

CodePudding user response：

Convert list to Series and it will work.

import pandas as pd
VID = ['00001', '05445', '987457', '15455'] 
IMG = ['00001', '05445', '987457'] 

df = pd.DataFrame({"video": pd.Series(VID), "image": pd.Series(IMG)})

    video   image
0   00001   00001
1   05445   05445
2   987457  987457
3   15455   NaN