Python turn a hash into a dataframe

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I have a hash file looks like this and the data is separated line by line:

Amy:0001:[{'name': 'Amy', 'age': '14', 'grade': '7', 'award': '0'}]

Carl:0024:[{'name': 'Carl', 'age': '12', 'grade': '6', 'award': '2'}, {'name': 'Carl', 'age': '18', 'grade': '12', 'award': '4'}, {'name': 'Carl', 'age': '13', 'grade': '6', 'award': '7'}]

and more ...

I want to have a dataframe that look like this:

           name     age      grade     award

Amy:0001    Amy     14        7         0

Carl:0024   Carl    12        6         2

Carl:0024   Carl    18        12        4

Carl:0024   Carl    13        6         7

I tried to strip the hash line by line

lines = [line.rstrip('n') for line in open("my_file.txt")]

edited Jan 4 at 18:28

Yuca

3,0792826

asked Jan 4 at 18:27

Matt-pow

155416

add a comment |

I have a hash file looks like this and the data is separated line by line:

Amy:0001:[{'name': 'Amy', 'age': '14', 'grade': '7', 'award': '0'}]

Carl:0024:[{'name': 'Carl', 'age': '12', 'grade': '6', 'award': '2'}, {'name': 'Carl', 'age': '18', 'grade': '12', 'award': '4'}, {'name': 'Carl', 'age': '13', 'grade': '6', 'award': '7'}]

and more ...

I want to have a dataframe that look like this:

           name     age      grade     award

Amy:0001    Amy     14        7         0

Carl:0024   Carl    12        6         2

Carl:0024   Carl    18        12        4

Carl:0024   Carl    13        6         7

I tried to strip the hash line by line

lines = [line.rstrip('n') for line in open("my_file.txt")]

edited Jan 4 at 18:28

Yuca

3,0792826

asked Jan 4 at 18:27

Matt-pow

155416

add a comment |

I have a hash file looks like this and the data is separated line by line:

Amy:0001:[{'name': 'Amy', 'age': '14', 'grade': '7', 'award': '0'}]

Carl:0024:[{'name': 'Carl', 'age': '12', 'grade': '6', 'award': '2'}, {'name': 'Carl', 'age': '18', 'grade': '12', 'award': '4'}, {'name': 'Carl', 'age': '13', 'grade': '6', 'award': '7'}]

and more ...

I want to have a dataframe that look like this:

           name     age      grade     award

Amy:0001    Amy     14        7         0

Carl:0024   Carl    12        6         2

Carl:0024   Carl    18        12        4

Carl:0024   Carl    13        6         7

I tried to strip the hash line by line

lines = [line.rstrip('n') for line in open("my_file.txt")]

edited Jan 4 at 18:28

Yuca

3,0792826

asked Jan 4 at 18:27

Matt-pow

155416

I have a hash file looks like this and the data is separated line by line:

Amy:0001:[{'name': 'Amy', 'age': '14', 'grade': '7', 'award': '0'}]

Carl:0024:[{'name': 'Carl', 'age': '12', 'grade': '6', 'award': '2'}, {'name': 'Carl', 'age': '18', 'grade': '12', 'award': '4'}, {'name': 'Carl', 'age': '13', 'grade': '6', 'award': '7'}]

and more ...

I want to have a dataframe that look like this:

           name     age      grade     award

Amy:0001    Amy     14        7         0

Carl:0024   Carl    12        6         2

Carl:0024   Carl    18        12        4

Carl:0024   Carl    13        6         7

I tried to strip the hash line by line

lines = [line.rstrip('n') for line in open("my_file.txt")]

python pandas dictionary hash

edited Jan 4 at 18:28

Yuca

3,0792826

asked Jan 4 at 18:27

Matt-pow

155416

edited Jan 4 at 18:28

Yuca

3,0792826

asked Jan 4 at 18:27

Matt-pow

155416

edited Jan 4 at 18:28

Yuca

3,0792826

edited Jan 4 at 18:28

Yuca

3,0792826

edited Jan 4 at 18:28

Yuca

3,0792826

asked Jan 4 at 18:27

Matt-pow

155416

asked Jan 4 at 18:27

Matt-pow

155416

asked Jan 4 at 18:27

Matt-pow

155416

add a comment |

2 Answers
2

active

oldest

votes

Start with an empty DataFrame:

df = pd.DataFrame(columns=['key','name','age','grade','award'])

Line by line read the hash file into the dataframe:

import json

with open(hash_path, 'r') as f:

    for line in f:

        key = ":".join(line.split(":", 2)[:2])

        rows = line.split(":", 2)[-1]

        # json requires double quotes for strings

        rows = json.loads(rows.replace("'",'"'))

        for row in rows:

            row['key'] = key

            df = df.append(pd.Series(row), ignore_index=True)

# set the 'key' column to the index

df.set_index('key', inplace=True)

edited Jan 4 at 18:55

answered Jan 4 at 18:49

chet-the-wizard

833514

add a comment |

Here's a solution using ast.literal_eval which doesn't require explicit line-by-line iteration. You should find it considerably more efficient.

from io import StringIO

from ast import literal_eval



x = """Amy:0001:[{'name': 'Amy', 'age': '14', 'grade': '7', 'award': '0'}]

Carl:0024:[{'name': 'Carl', 'age': '12', 'grade': '6', 'award': '2'}, {'name': 'Carl', 'age': '18', 'grade': '12', 'award': '4'}, {'name': 'Carl', 'age': '13', 'grade': '6', 'award': '7'}]"""



df = pd.read_csv(StringIO(x), delimiter='[', header=None, names=['id', 'data'])



df['id'] = df['id'].str[:-1]

df['data'] = df['data'].map(lambda x: literal_eval(f'[{x}'))



lens = df['data'].str.len()



df = pd.DataFrame({'id': np.repeat(df['id'].values, lens)})

       .join(pd.DataFrame(list(chain.from_iterable(df['data']))))

       .set_index('id')



print(df)



          age award grade  name

id                             

Amy:0001   14     0     7   Amy

Carl:0024  12     2     6  Carl

Carl:0024  18     4    12  Carl

Carl:0024  13     7     6  Carl

edited Jan 4 at 21:25

answered Jan 4 at 19:07

jpp

103k2167117

add a comment |

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2 Answers
2

active

oldest

votes

2 Answers
2

active

oldest

votes

Start with an empty DataFrame:

df = pd.DataFrame(columns=['key','name','age','grade','award'])

Line by line read the hash file into the dataframe:

import json

with open(hash_path, 'r') as f:

    for line in f:

        key = ":".join(line.split(":", 2)[:2])

        rows = line.split(":", 2)[-1]

        # json requires double quotes for strings

        rows = json.loads(rows.replace("'",'"'))

        for row in rows:

            row['key'] = key

            df = df.append(pd.Series(row), ignore_index=True)

# set the 'key' column to the index

df.set_index('key', inplace=True)

edited Jan 4 at 18:55

answered Jan 4 at 18:49

chet-the-wizard

833514

add a comment |

Start with an empty DataFrame:

df = pd.DataFrame(columns=['key','name','age','grade','award'])

Line by line read the hash file into the dataframe:

import json

with open(hash_path, 'r') as f:

    for line in f:

        key = ":".join(line.split(":", 2)[:2])

        rows = line.split(":", 2)[-1]

        # json requires double quotes for strings

        rows = json.loads(rows.replace("'",'"'))

        for row in rows:

            row['key'] = key

            df = df.append(pd.Series(row), ignore_index=True)

# set the 'key' column to the index

df.set_index('key', inplace=True)

edited Jan 4 at 18:55

answered Jan 4 at 18:49

chet-the-wizard

833514

add a comment |

Start with an empty DataFrame:

df = pd.DataFrame(columns=['key','name','age','grade','award'])

Line by line read the hash file into the dataframe:

import json

with open(hash_path, 'r') as f:

    for line in f:

        key = ":".join(line.split(":", 2)[:2])

        rows = line.split(":", 2)[-1]

        # json requires double quotes for strings

        rows = json.loads(rows.replace("'",'"'))

        for row in rows:

            row['key'] = key

            df = df.append(pd.Series(row), ignore_index=True)

# set the 'key' column to the index

df.set_index('key', inplace=True)

edited Jan 4 at 18:55

answered Jan 4 at 18:49

chet-the-wizard

833514

Start with an empty DataFrame:

df = pd.DataFrame(columns=['key','name','age','grade','award'])

Line by line read the hash file into the dataframe:

import json

with open(hash_path, 'r') as f:

    for line in f:

        key = ":".join(line.split(":", 2)[:2])

        rows = line.split(":", 2)[-1]

        # json requires double quotes for strings

        rows = json.loads(rows.replace("'",'"'))

        for row in rows:

            row['key'] = key

            df = df.append(pd.Series(row), ignore_index=True)

# set the 'key' column to the index

df.set_index('key', inplace=True)

edited Jan 4 at 18:55

answered Jan 4 at 18:49

chet-the-wizard

833514

edited Jan 4 at 18:55

answered Jan 4 at 18:49

chet-the-wizard

833514

answered Jan 4 at 18:49

chet-the-wizard

833514

answered Jan 4 at 18:49

chet-the-wizard

833514

add a comment |

Here's a solution using ast.literal_eval which doesn't require explicit line-by-line iteration. You should find it considerably more efficient.

from io import StringIO

from ast import literal_eval



x = """Amy:0001:[{'name': 'Amy', 'age': '14', 'grade': '7', 'award': '0'}]

Carl:0024:[{'name': 'Carl', 'age': '12', 'grade': '6', 'award': '2'}, {'name': 'Carl', 'age': '18', 'grade': '12', 'award': '4'}, {'name': 'Carl', 'age': '13', 'grade': '6', 'award': '7'}]"""



df = pd.read_csv(StringIO(x), delimiter='[', header=None, names=['id', 'data'])



df['id'] = df['id'].str[:-1]

df['data'] = df['data'].map(lambda x: literal_eval(f'[{x}'))



lens = df['data'].str.len()



df = pd.DataFrame({'id': np.repeat(df['id'].values, lens)})

       .join(pd.DataFrame(list(chain.from_iterable(df['data']))))

       .set_index('id')



print(df)



          age award grade  name

id                             

Amy:0001   14     0     7   Amy

Carl:0024  12     2     6  Carl

Carl:0024  18     4    12  Carl

Carl:0024  13     7     6  Carl

edited Jan 4 at 21:25

answered Jan 4 at 19:07

jpp

103k2167117

add a comment |

Here's a solution using ast.literal_eval which doesn't require explicit line-by-line iteration. You should find it considerably more efficient.

from io import StringIO

from ast import literal_eval



x = """Amy:0001:[{'name': 'Amy', 'age': '14', 'grade': '7', 'award': '0'}]

Carl:0024:[{'name': 'Carl', 'age': '12', 'grade': '6', 'award': '2'}, {'name': 'Carl', 'age': '18', 'grade': '12', 'award': '4'}, {'name': 'Carl', 'age': '13', 'grade': '6', 'award': '7'}]"""



df = pd.read_csv(StringIO(x), delimiter='[', header=None, names=['id', 'data'])



df['id'] = df['id'].str[:-1]

df['data'] = df['data'].map(lambda x: literal_eval(f'[{x}'))



lens = df['data'].str.len()



df = pd.DataFrame({'id': np.repeat(df['id'].values, lens)})

       .join(pd.DataFrame(list(chain.from_iterable(df['data']))))

       .set_index('id')



print(df)



          age award grade  name

id                             

Amy:0001   14     0     7   Amy

Carl:0024  12     2     6  Carl

Carl:0024  18     4    12  Carl

Carl:0024  13     7     6  Carl

edited Jan 4 at 21:25

answered Jan 4 at 19:07

jpp

103k2167117

add a comment |

Here's a solution using ast.literal_eval which doesn't require explicit line-by-line iteration. You should find it considerably more efficient.

from io import StringIO

from ast import literal_eval



x = """Amy:0001:[{'name': 'Amy', 'age': '14', 'grade': '7', 'award': '0'}]

Carl:0024:[{'name': 'Carl', 'age': '12', 'grade': '6', 'award': '2'}, {'name': 'Carl', 'age': '18', 'grade': '12', 'award': '4'}, {'name': 'Carl', 'age': '13', 'grade': '6', 'award': '7'}]"""



df = pd.read_csv(StringIO(x), delimiter='[', header=None, names=['id', 'data'])



df['id'] = df['id'].str[:-1]

df['data'] = df['data'].map(lambda x: literal_eval(f'[{x}'))



lens = df['data'].str.len()



df = pd.DataFrame({'id': np.repeat(df['id'].values, lens)})

       .join(pd.DataFrame(list(chain.from_iterable(df['data']))))

       .set_index('id')



print(df)



          age award grade  name

id                             

Amy:0001   14     0     7   Amy

Carl:0024  12     2     6  Carl

Carl:0024  18     4    12  Carl

Carl:0024  13     7     6  Carl

edited Jan 4 at 21:25

answered Jan 4 at 19:07

jpp

103k2167117

Here's a solution using ast.literal_eval which doesn't require explicit line-by-line iteration. You should find it considerably more efficient.

from io import StringIO

from ast import literal_eval



x = """Amy:0001:[{'name': 'Amy', 'age': '14', 'grade': '7', 'award': '0'}]

Carl:0024:[{'name': 'Carl', 'age': '12', 'grade': '6', 'award': '2'}, {'name': 'Carl', 'age': '18', 'grade': '12', 'award': '4'}, {'name': 'Carl', 'age': '13', 'grade': '6', 'award': '7'}]"""



df = pd.read_csv(StringIO(x), delimiter='[', header=None, names=['id', 'data'])



df['id'] = df['id'].str[:-1]

df['data'] = df['data'].map(lambda x: literal_eval(f'[{x}'))



lens = df['data'].str.len()



df = pd.DataFrame({'id': np.repeat(df['id'].values, lens)})

       .join(pd.DataFrame(list(chain.from_iterable(df['data']))))

       .set_index('id')



print(df)



          age award grade  name

id                             

Amy:0001   14     0     7   Amy

Carl:0024  12     2     6  Carl

Carl:0024  18     4    12  Carl

Carl:0024  13     7     6  Carl

edited Jan 4 at 21:25

answered Jan 4 at 19:07

jpp

103k2167117

edited Jan 4 at 21:25

answered Jan 4 at 19:07

jpp

103k2167117

answered Jan 4 at 19:07

jpp

103k2167117

answered Jan 4 at 19:07

jpp

103k2167117

add a comment |

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