hdf

问题 I have several comma-separated data files that I want to load into an xarray dataset. Each row in each file represents a different spatial value of a field in a fixed grid, and every file represents a different point in time. The grid spacing is fixed and unchanging in time. The spacing of the grid is not uniform. The ultimate goal is to compute max_{x, y} { std_t[ value(x, y, t) * sqrt(y **2 + x ** 2)] } , where sqrt is the square root, std_t is standard deviation with respect to time and

问题 I have several comma-separated data files that I want to load into an xarray dataset. Each row in each file represents a different spatial value of a field in a fixed grid, and every file represents a different point in time. The grid spacing is fixed and unchanging in time. The spacing of the grid is not uniform. The ultimate goal is to compute max_{x, y} { std_t[ value(x, y, t) * sqrt(y **2 + x ** 2)] } , where sqrt is the square root, std_t is standard deviation with respect to time and

问题 This is a follow up to this stackoverflow question Column missing when trying to open hdf created by pandas in h5py Where I am trying to create save a large amount of data onto a disk (too large to fit into memory), and retrieve sepecific rows of the data using indices. One of the solutions given in the linked post is to create a seperate key for every every row. At the moment I can only think of iterating through each row, and setting the keys directly. For example, if this is my data

问题 I have a hdf file and want to extract data from it. For some reason i cant able to extract latitude and longitude values: the code that i tried is : from pyhdf import SD hdf = SD.SD('MOD10C2.A2001033.006.2016092173057.hdf') data = hdf.select('Eight_Day_CMG_Snow_Cover') lat = (hdf.select('Latitude'))[:] it gives me an error: HDF4Error: select: non-existent dataset I tried with: lat = (hdf.select('Lat'))[:] still does not help! data can be found in this link any help will be highly appreciated!

问题 I have a hdf file and want to extract data from it. For some reason i cant able to extract latitude and longitude values: the code that i tried is : from pyhdf import SD hdf = SD.SD('MOD10C2.A2001033.006.2016092173057.hdf') data = hdf.select('Eight_Day_CMG_Snow_Cover') lat = (hdf.select('Latitude'))[:] it gives me an error: HDF4Error: select: non-existent dataset I tried with: lat = (hdf.select('Lat'))[:] still does not help! data can be found in this link any help will be highly appreciated!

问题 I have a hdf file and want to extract data from it. For some reason i cant able to extract latitude and longitude values: the code that i tried is : from pyhdf import SD hdf = SD.SD('MOD10C2.A2001033.006.2016092173057.hdf') data = hdf.select('Eight_Day_CMG_Snow_Cover') lat = (hdf.select('Latitude'))[:] it gives me an error: HDF4Error: select: non-existent dataset I tried with: lat = (hdf.select('Lat'))[:] still does not help! data can be found in this link any help will be highly appreciated!

问题 I have a hdf file and want to extract data from it. For some reason i cant able to extract latitude and longitude values: the code that i tried is : from pyhdf import SD hdf = SD.SD('MOD10C2.A2001033.006.2016092173057.hdf') data = hdf.select('Eight_Day_CMG_Snow_Cover') lat = (hdf.select('Latitude'))[:] it gives me an error: HDF4Error: select: non-existent dataset I tried with: lat = (hdf.select('Lat'))[:] still does not help! data can be found in this link any help will be highly appreciated!

问题 I have a table in Hive CREATE TABLE tab_data ( rec_id INT, rec_name STRING, rec_value DECIMAL(3,1), rec_created TIMESTAMP ) STORED AS PARQUET; and I want to populate this table with data in .csv files like these 10|customer1|10.0|2016-09-07 08:38:00.0 20|customer2|24.0|2016-09-08 10:45:00.0 30|customer3|35.0|2016-09-10 03:26:00.0 40|customer1|46.0|2016-09-11 08:38:00.0 50|customer2|55.0|2016-09-12 10:45:00.0 60|customer3|62.0|2016-09-13 03:26:00.0 70|customer1|72.0|2016-09-14 08:38:00.0 80

问题 There is an HDF file 'file.h5' and the key name of a pandas DataFrame (or a Series) saved into it is 'df'. How can one determine in what format (i.e. ‘fixed’ or ‘table’) was 'df' saved into the file? Thank you for your help! 回答1: A bit late but maybe someone else may find it helpful. You can parse the output of HDFStore.info(). Objects in table format have the type appendable : >>> print(h5_table.info()) <class 'pandas.io.pytables.HDFStore'> File path: /tmp/df_table.h5 /df frame_table (typ-

问题 I am following this link to set up Nifi putHDFS to write to Azure Data Lake.Connecting to Azure Data Lake from a NiFi dataflow The Nifi is within HDF 3.1 VM and the Nifi version is 1.5. We got the jar files mentioned in the above link, from a HD Insight(v 3.6, which supports hadoop 2.7) head node, these jars are: adls2-oauth2-token-provider-1.0.jar azure-data-lake-store-sdk-2.1.4.jar hadoop-azure-datalake.jar jackson-core-2.2.3.jar okhttp-2.4.0.jar okio-1.4.0.jar And they are copied to the