data-conversion

How to convert a simple string to a null-terminated one? Example: Example string: "Test message" Here are the bytes: 54 65 73 74 20 6D 65 73 73 61 67 65 I need string with bytes like follows: 54 00 65 00 73 00 74 00 20 00 6D 00 65 00 73 00 73 00 61 00 67 00 65 00 00 I could use loops, but will be too ugly code. How can I make this conversion by native methods? It looks like you want a null-terminated Unicode string. If the string is stored in a variable str , this should work: var bytes = System.Text.Encoding.Unicode.GetBytes(str + "\0"); ( See it run .) Note that the resulting array will have

I have this XML file: <?xml version="1.0" encoding="UTF-8" standalone="yes"?> <ns3:BOX xmlns="urn:loc.gov:item" xmlns:ns2="urn:loc.gov:box" xmlns:ns3="http://www.example.com/inverter" xmlns:ns4="urn:loc.gov:xyz"> <ns3:Item> <Description>ITEM1</Description> <PackSizeNumeric>6</PackSizeNumeric> <ns2:BuyersItemIdentification> <ID>75847589</ID> </ns2:BuyersItemIdentification> <ns2:CommodityClassification> <CommodityCode>856952</CommodityCode> </ns2:CommodityClassification> <ns2:AdditionalItemProperty> <Name>Weight</Name> <Value>0</Value> </ns2:AdditionalItemProperty> <ns2:AdditionalItemProperty>

I'm working with pandas and I used the groupby: group = df_crimes_query.groupby(["CrimeDateTime", "WeaponFactor"]).size() group.head(20) CrimeDateTime WeaponFactor 2016-01-01 FIREARM 11 HANDS 26 KNIFE 3 OTHER 11 UNDEFINED 102 2016-01-02 FIREARM 10 HANDS 21 KNIFE 8 OTHER 6 UNDEFINED 68 2016-01-03 FIREARM 12 HANDS 13 KNIFE 6 OTHER 5 UNDEFINED 73 2016-01-04 FIREARM 11 HANDS 10 KNIFE 1 OTHER 3 UNDEFINED 84 dtype: int64 The type of it is a Series: type(group) pandas.core.series.Series I would like a dataframe about like this: CrimeDateTime FIREARM HANDS KNIFE OTHER UNDEFINED 2016-01-01 11 26 3 11