How do I read a fixed width format text file in pandas?
pandas.read_fwf() was added in pandas 0.7.3 (April 2012) to handle fixed-width files. API reference An example from other question
pandas.read_fwf() was added in pandas 0.7.3 (April 2012) to handle fixed-width files. API reference An example from other question
Spark’s substr function can handle fixed-width columns, for example: df = spark.read.text(“/tmp/sample.txt”) df.select( df.value.substr(1,3).alias(‘id’), df.value.substr(4,8).alias(‘date’), df.value.substr(12,3).alias(‘string’), df.value.substr(15,4).cast(‘integer’).alias(‘integer’) ).show() will result in: +—+——–+——+——-+ | id| date|string|integer| +—+——–+——+——-+ |001|01292017| you| 1234| |002|01302017| me| 5678| +—+——–+——+——-+ Having splitted columns you can reformat and use them as in normal spark dataframe.
Tables have difficult rules about distributing the space of the columns because they distribute space dependent on the content of the cells by default. Calc (atm) just wont work with that. What you can do however is to set the table-layout attribute for the table to force the child td elements to get the exact … Read more
See: http://jsfiddle.net/qx32C/36/ .lineContainer { overflow: hidden; /* clear the float */ border: 1px solid #000 } .lineContainer div { height: 20px } .left { width: 100px; float: left; border-right: 1px solid #000 } .right { overflow: hidden; background: #ccc } <div class=”lineContainer”> <div class=”left”>left</div> <div class=”right”>right</div> </div> Why did I replace margin-left: 100px with overflow: … Read more
I would use a flat file parser like flatworm instead of reinventing the wheel: it has a clean API, is simple to use, has decent error handling and a simple file format descriptor. Another option is jFFP but I prefer the first one.
Until someone implements this in pandas, you can use the tabulate package: import pandas as pd from tabulate import tabulate def to_fwf(df, fname): content = tabulate(df.values.tolist(), list(df.columns), tablefmt=”plain”) open(fname, “w”).write(content) pd.DataFrame.to_fwf = to_fwf
When you decide between fixed width and fluid width you need to think in terms of your ENTIRE page. Generally, you want to pick one or the other, but not both. The examples you listed in your question are, in-fact, in the same fixed-width page. In other words, the Scaffolding page is using a fixed-width … Read more
Use FileHelpers. Example: [FixedLengthRecord()] public class MyData { [FieldFixedLength(8)] public string someData; [FieldFixedLength(16)] public int SomeNumber; [FieldFixedLength(12)] [FieldTrim(TrimMode.Right)] public string someMoreData; } Then, it’s as simple as this: var engine = new FileHelperEngine<MyData>(); // To Read Use: var res = engine.ReadFile(“FileIn.txt”); // To Write Use: engine.WriteFile(“FileOut.txt”, res);
The method of Srikar works very well, if you know both height and width of your new Size. If you for example know only the width you want to scale to and don’t care about the height you first have to calculate the scale factor of the height. +(UIImage*)imageWithImage: (UIImage*) sourceImage scaledToWidth: (float) i_width { … Read more
This is a fixed width file. Use read.fwf() to read it: x <- read.fwf( file=url(“http://www.cpc.ncep.noaa.gov/data/indices/wksst8110.for”), skip=4, widths=c(12, 7, 4, 9, 4, 9, 4, 9, 4)) head(x) V1 V2 V3 V4 V5 V6 V7 V8 V9 1 03JAN1990 23.4 -0.4 25.1 -0.3 26.6 0.0 28.6 0.3 2 10JAN1990 23.4 -0.8 25.2 -0.3 26.6 0.1 28.6 0.3 … Read more