Database matlab 数据文件到 pandas DataFrame

我找到了两种方法:scipy或mat4py.

1. mat4py

从MAT文件加载数据

函数loadmat将MAT文件中存储的所有变量加载到

示例:将MAT文件加载到Python数据 struct 中:

data = loadmat('datafile.mat')

发件人:

https://pypi.python.org/pypi/mat4py/0.1.0个

2. Scipy:

示例:

import numpy as np
from scipy.io import loadmat  # this is the SciPy module that loads mat-files
import matplotlib.pyplot as plt
from datetime import datetime, date, time
import pandas as pd

mat = loadmat('measured_data.mat')  # load mat-file
mdata = mat['measuredData']  # variable in mat file
mdtype = mdata.dtype  # dtypes of structures are "unsized objects"
# * SciPy reads in structures as structured NumPy arrays of dtype object
# * The size of the array is the size of the structure array, not the number
#   elements in any particular field. The shape defaults to 2-dimensional.
# * For convenience make a dictionary of the data using the names from dtypes
# * Since the structure has only one element, but is 2-D, index it at [0, 0]
ndata = {n: mdata[n][0, 0] for n in mdtype.names}
# Reconstruct the columns of the data table from just the time series
# Use the number of intervals to test if a field is a column or metadata
columns = [n for n, v in ndata.iteritems() if v.size == ndata['numIntervals']]
# now make a data frame, setting the time stamps as the index
df = pd.DataFrame(np.concatenate([ndata[c] for c in columns], axis=1),
                  index=[datetime(*ts) for ts in ndata['timestamps']],
                  columns=columns)

发件人:

http://poquitopicante.blogspot.fr/2014/05/loading-matlab-mat-file-into-pandas.html个

3. 最后，您可以使用PyHogs，但仍可以使用scipy:

正在读取复杂的.mat个文件.

本笔记本显示了一个读取Matlab.mat文件的示例， 使用循环将数据转换为可用的字典，这是一个简单的图 数据的一部分.

http://pyhogs.github.io/reading-mat-files.html