英文:
Dictionary to Dataframe with list as value
问题
import pandas as pddf = pd.DataFrame.from_dict({'pl': pl, 'pr': pr}, orient='index').T
英文:
I am trying to create a dataframe from two dictionaries with matching keys with the values in neighboring columns.
I have two dictionaries:
pl = {'seq1' : ['actgcta', 'cggctatcg'], 'seq2': ['cgatcgatca'], 'seq3': ['cgatcagt', 'cgataataat']}pr = {'seq1' : ['cagtatacga', 'attacgat', 'atcgactagt'], 'seq2': ['cgatcgatca'], 'seq3': ['cgatcagt']}
I am trying to create a dataframe that looks like this (please forgive the crude figure):
seq1 |['actgcta','cggctatcg'] |['cagtatacga', 'attacgat', 'atcgactagt']--------------------------------------------------------------------------seq2 |['cgatcgatca'] |['cgatcgatca']--------------------------------------------------------------------------seq3 |['cgatcagt', 'cgataataat'] |['cgatcagt']
I have tried working with pd.DataFrame , pd.DataFrame.from_dict , and played with various orient args, but have had no success.
答案1
得分: 1
一种使用 pandas.concat 的方法：
df = pd.concat(map(pd.Series, [pl, pr]), axis=1)
输出：
| | 0 | 1 ||-------|---------------------|-------------------------------------------|| seq1 | [actgcta, cggctatcg] | [cagtatacga, attacgat, atcgactagt] || seq2 | [cgatcgatca] | [cgatcgatca] || seq3 | [cgatcagt, cgataataat]| [cgatcagt] |
英文:
One way using pandas.concat:
df = pd.concat(map(pd.Series, [pl, pr]), axis=1)
Output:
0 1seq1 [actgcta, cggctatcg] [cagtatacga, attacgat, atcgactagt]seq2 [cgatcgatca] [cgatcgatca]seq3 [cgatcagt, cgataataat] [cgatcagt]
答案2
得分: 0
很遗憾，要将字典导入数据框，你的列表必须具有相同的长度，而它们目前并没有。因此，我们首先需要将这些列表放入一个列表中。然后，我们可以通过简单的连接操作合并数据框：
英文:
Unfortunately, to import the dictionaries into dataframes, you r lists must be of the same length, which they are not. So we must first put the lists into a single list of list. Then we can merge the dataframes with simple concatenation:
import pandas as pdpl = {'seq1' : ['actgcta', 'cggctatcg'], 'seq2': ['cgatcgatca'], 'seq3': ['cgatcagt', 'cgataataat']}pr = {'seq1' : ['cagtatacga', 'attacgat', 'atcgactagt'], 'seq2': ['cgatcgatca'], 'seq3': ['cgatcagt']}for keys in pl.keys():pl[keys] = [pl[keys]]for keys in pr.keys():pr[keys] = [pr[keys]]df = pd.DataFrame(pl)df1 = pd.DataFrame(pr)df2 = pd.concat([df, df1])print(df2.transpose())</details>
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