CODEWITHSUNDEEP
pythondataframetreenested
sanyi14ka
sanyi14ka

Reputation: 829

How to parse a tree like data into a nested list in Python?

I have some files which have tree like structure. For example:

A
  Result
    a11
    a12
  Lolim
    a21
    a22
  Uplim
    a31
    a32
B
  Result
    b11
    b12
  Lolim
    b21
    b22

I am interested in parsing this files in order to obtain a dataframe which looks like this:

Name Result Lolim Uplim
A    a12    a22   a32
B    b12    b22   NA

My idea was to split somehow the file in two parts: A and B. And after that split each one in subcategories. For A would be Result, Lolim and Uplim and for B Result and Lolim. Finally each subcategory in 2 parts. Therefore I will end up with a nested list, and than I will be able to create a dataframe. But I don't know how to obtain this nested list.

Or is there another method for this? Can you recommend me modules or functions which can be useful?

Upvotes: 3

Views: 326

Answers (1)

Spherical Cowboy
Spherical Cowboy

Reputation: 566

import collections
import pandas as pd

with open("data_tree.dat", "r") as data:
    dct = collections.OrderedDict()
    key = ""
    sub_key = ""
    for line in data:
        if " " not in line:  # single space
            key = line.strip()
            dct[key] = collections.OrderedDict()
        elif " " * 4 in line and " " * 6 not in line:  # 4 spaces
            sub_key = line.strip()
            dct[key][sub_key] = ""
        elif " " * 6 in line:  # 6 spaces
            item = line.strip()
            dct[key][sub_key] = item  # overwrite, last element only

df = pd.DataFrame.from_dict(dct).transpose()
df.columns.names = ["Name"]
df = df[["Result", "Lolim", "Uplim"]]  # if column order matters
df = df.fillna("NA")  # in case you want NA and not NaN

print(df)

Output:

Name Result Lolim Uplim
A       a12   a22   a32
B       b12   b22   NA

This assumes that data_tree.dat looks like this and is contained within the same folder as the .py file containing the above code.

Or as a function:

import collections
import pandas as pd


def dat_to_df(path_to_file):
    with open(path_to_file, "r") as data:
        dct = collections.OrderedDict()
        key = ""
        sub_key = ""
        for line in data:
            if " " not in line:
                key = line.strip()
                dct[key] = collections.OrderedDict()
            elif " " * 4 in line and " " * 6 not in line:
                sub_key = line.strip()
                dct[key][sub_key] = ""
            elif " " * 6 in line:
                item = line.strip()
                dct[key][sub_key] = item

    df = pd.DataFrame.from_dict(dct).transpose()
    df.columns.names = ["Name"]
    df = df[["Result", "Lolim", "Uplim"]]
    return df.fillna("NA")

dataframe = dat_to_df("data_tree.dat")

print(dataframe)

Upvotes: 2

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