I have a dataframe with mixed types. I have the columns, x, y, z, matrix, where matrix is a numpy matrix
10 10 10 [[1,2,3],[4,5,6],[7,8,9]]
12 12 12 [[1,2,3],[4,5,6],[7,8,9]]
14 14 14 [[1,2,3],[4,5,6],[7,8,9]]
I want to take the value of the matrix in index row 1 column index 1 (5) for plotting together with x, y, z
I have tried the following, but it does not work
print(df["matrix"][:][1,1])
new = df_max_timestep
tangential_stress = []
for value in df_max_timestep["rotated stress tensor"]:
tangential_stress.append(value[1,1])
new["Tangential stress"] = tangential_stress
Try to get the matrix elements by string accessor .str[], as follows:
df['matrix'].str[1].str[1]
Result:
0 5
1 5
2 5
Name: matrix, dtype: int64
Data Setup
data = {'x': [10, 12, 14],
'y': [10, 12, 14],
'z': [10, 12, 14],
'matrix': [np.array([[1,2,3],[4,5,6],[7,8,9]]),
np.array([[1,2,3],[4,5,6],[7,8,9]]),
np.array([[1,2,3],[4,5,6],[7,8,9]])]}
df = pd.DataFrame(data)
print(df)
x y z matrix
0 10 10 10 [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
1 12 12 12 [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
2 14 14 14 [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
You can first stack the arrays. Then you will be able to then handle them as numpy arrays:
import pandas as pd
import numpy as np
df = pd.DataFrame([[10, 10, 10, np.array([[1,2,3],[4,5,6],[7,8,9]])],
[12, 12, 12, np.array([[1,2,3],[4,5,6],[7,8,9]])],
[14, 14, 14, np.array([[1,2,3],[4,5,6],[7,8,9]])],],
columns=['x', 'y', 'z', 'matrix']
)
np.stack(df['matrix'])[:, 1,1]
output:
array([5, 5, 5])
example of assignment as new column:
>>> df['new'] = np.stack(df['matrix'])[:, 1,1]
>>> df
x y z matrix new
0 10 10 10 [[1, 2, 3], [4, 5, 6], [7, 8, 9]] 5
1 12 12 12 [[1, 2, 3], [4, 5, 6], [7, 8, 9]] 5
2 14 14 14 [[1, 2, 3], [4, 5, 6], [7, 8, 9]] 5
import plotly.express as px
df['matrix_center'] = np.stack(df['matrix'])[:, 1,1]
px.scatter_3d(df, x='x', y='y', z='z', color='matrix_center')
