Python Pandas DataFrame 将每一行的列转换为单个列作为 Pandas 系列

Question

I am trying to get the data of Pandas.DataFrame (df) into the shape (3,1) with each row being a Pandas.Series. When I run my code I keep getting NaN in every single cell instead of the Pandas.Series.

import pandas as pd
import numpy as np
df = pd.DataFrame(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]),columns=['a', 'b', 'c'])
s = pd.DataFrame(np.zeros(len(df.index))) #creates desired shape

for index, row in df.iterrows():
    print(row)
    s.iloc[index] = pd.Series(row)
s.head()

Answer 1

This might be what you want

X_train = np.array(pd.Series(df.values.tolist())).reshape(3, 1)

print(X_train.shape)
(3, 1)

Answer 2

You shouldn't set the location to a value. Instead consider creating a DataFrame as

s = pd.DataFrame(columns=['new_column']) # Empty Dataframe with 1 Column

Then you can append your rows with

s = s.append({'new_column': row}, ignore_index=True) # Add the Series as an Element