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efueyo
Asked: 2020-08-09 10:57:37 +0800 CST 2020-08-09 10:57:37 +0800 CST

Python Pandas error "ValueError: can not merge DataFrame with instance of type <class 'list'>"

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I need to add data from other dataframes to a dataframe, using the merge function, to ensure that it only takes those values ​​whose indices have the same date. The statement that I show below returns the error mentioned in the Title.

df_total = pd.merge(cotiz_diaria, [df, df1, df2, df3, df4, df5, df6, df7, df8, df9, df10, df11, df12], left_index=True, right_index=True) 
df_df_total

The error seems to indicate that it doesn't support df lists.

How else could I do this join, other than adding each dataframe one by one?

python

1 Answers

  1. Best Answer

    Indeed, your diagnosis is correct. What happens is that merge()it does not accept a list of Dataframeat most two of these objects is allowed to be passed to it. But you can iterate over the list and do the process of merge. For example:

    import pandas as pd
import numpy as np

df1 = pd.DataFrame(np.array([['a', 1, 2]]))
df2 = pd.DataFrame(np.array([['b', 3, 4]]))
df3 = pd.DataFrame(np.array([['c', 5, 6]]))

dfs = [df1, df2, df3]

    We have created a list dfscontaining 3 DataFrame, now we can do the merge:

    dfs = iter(dfs)
df_final = next(dfs)
for df_ in dfs:
    df_final = df_final.merge(df_, left_index=True, right_index=True)

print(df_final)

  0_x 1_x 2_x 0_y 1_y 2_y  0  1  2
0   a   1   2   b   3   4  c  5  6

    Detail:

    • With we dfs = iter(dfs)convert the list into a iterador, this is because of the way we are going to process, as we need the first element on the one hand and then the rest, it is preferable to do it this way and avoid making copies of lists.

    • With df_final = next(dfs) we initialize the DataFrameend with the first object of the list

    • Then we simply iterate over the next elements of the list and with it df_final = df_final.merge(df_, left_index=True, right_index=True)we do the one mergeof each object.

    An identical result but with fewer lines of code is to use the functionreduce()

    from functools import reduce

dfs = [df1, df2, df3]
df_final = reduce(lambda left,right: pd.merge(left,right,left_index=True, right_index=True), dfs)
print(df_final)
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