reading tab-delimited data without header in pandas
csv, dataframe, pandas, python
Solution
I think you are getting the it read correctly, but:
- See: change pandas 0.13.0 "print dataframe" to print dataframe like in earlier versions, this is what pandas do in the older versions. So, update will solve it.
- You can use `ipython notebook`, where `DataFrames` will show up as HTML tables.
- You can use `df.head(5)` (similar to `r`'s `head`) to get the first a few rows just to make sure your `DataFrame` is correct.
Problem
I'm having trouble using `pandas` to open tab-delimited data without headers. My test data (actually contains 200 lines, of which I am showing the first 10): ``` Tag19184 CTAAC hffef 1 a 36 - chr1 10006 0 36M 36 Tag19184 CTAAC hffef 1 a 36 - chr1 10012 0 36M 36 Tag19184 CTAAC hffef 1 a 36 - chr1 10018 0 36M 36 Tag19184 CTAAC hffef 1 a 36 - chr1 10024 0 36M 36 Tag19184 CTAAC hffef 1 a 36 - chr1 10030 0 36M 36 Tag19184 CTAAC hffef 1 a 36 - chr1 10036 0 36M 36 Tag19184 CTAAC hffef 1 a 36 - chr1 10042 0 36M 36 Tag20198 CTAAC hffef 1 a 36 - chr1 10048 0 36M 36 Tag20198 CTAAC hffef 1 a 36 - chr1 10054 0 36M 36 Tag45093 CTAAC hffef 1 a 36 - chr1 10060 0 36M 36 ``` My code: ``` import pandas as pd df = pd.read_csv('in_test.txt',sep='\t',header=None) print df ``` However, I get the following output, which I don't think I can use to further process data (?): ``` <class 'pandas.core.frame.DataFrame'> Int64Index: 200 entries, 0 to 199 Data columns: X.1 200 non-null values X.2 200 non-null values X.3 200 non-null values X.4 200 non-null values X.5 200 non-null values X.6 200 non-null values X.7 200 non-null values X.8 200 non-null values X.9 200 non-null values X.10 200 non-null values X.11 200 non-null values X.12 200 non-null values dtypes: int64(5), object(7) ``` The tutorial here suggests that `print df` should just give me the corresponding data frame. What am I doing wrong?