Update这是 pandas 文档中推荐的方法:https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html#external-compatibility https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html#external-compatibility
From https://github.com/pandas-dev/pandas/issues/9636 https://github.com/pandas-dev/pandas/issues/9636(谢谢约翰·高尔特 https://stackoverflow.com/users/2137255/john-galt向我指出此资源):
R 的 HDF5 导出示例
import numpy as np
import pandas as pd
np.random.seed(1)
df = pd.DataFrame({"first": np.random.rand(100),
"second": np.random.rand(100),
"class": np.random.randint(0, 2, (100,))},
index=range(100))
print(df.head())
store = pd.HDFStore("transfer.hdf5", "w", complib=str("zlib"), complevel=5)
store.put("dataframe", df, data_columns=df.columns)
store.close()
Output:
class first second
0 0 0.417022 0.326645
1 0 0.720324 0.527058
2 1 0.000114 0.885942
3 1 0.302333 0.357270
4 1 0.146756 0.908535
In R:
# Load values and column names for all datasets from corresponding nodes and
# insert them into one data.frame object.
library(rhdf5)
loadhdf5data <- function(h5File) {
listing <- h5ls(h5File)
# Find all data nodes, values are stored in *_values and corresponding column
# titles in *_items
data_nodes <- grep("_values", listing$name)
name_nodes <- grep("_items", listing$name)
data_paths = paste(listing$group[data_nodes], listing$name[data_nodes], sep = "/")
name_paths = paste(listing$group[name_nodes], listing$name[name_nodes], sep = "/")
columns = list()
for (idx in seq(data_paths)) {
data <- data.frame(t(h5read(h5File, data_paths[idx])))
names <- t(h5read(h5File, name_paths[idx]))
entry <- data.frame(data)
colnames(entry) <- names
columns <- append(columns, entry)
}
data <- data.frame(columns)
return(data)
}
现在您可以导入 DataFrame:
> data = loadhdf5data("transfer.hdf5")
> head(data)
first second class
1 0.4170220047 0.3266449 0
2 0.7203244934 0.5270581 0
3 0.0001143748 0.8859421 1
4 0.3023325726 0.3572698 1
5 0.1467558908 0.9085352 1
6 0.0923385948 0.6233601 1