将字典{"grammer":["Python","C","Java","GO",np.nan,"SQL","PHP","Python"], "score":[1,2,np.nan,4,5,6,7,10]}创建为Dataframe并打印

import pandas as pd
import numpy as np

data = {"grammer":["Python","C","Java","GO",np.nan,"SQL","PHP","Python"], "score":[1,2,np.nan,4,5,6,7,10]}
df = pd.DataFrame(data)
print(df)

输出结果为：

  grammer  score
0  Python    1.0
1       C    2.0
2    Java    NaN
3      GO    4.0
4     NaN    5.0
5     SQL    6.0
6     PHP    7.0
7  Python   10.0

相关问题

1.将下面的字典创建为DataFrame data+=+{"grammer":["Python","C","Java","GO",np.nan,"SQL","PHP","Python"],

以下是将字典创建为DataFrame的代码示例：

import pandas as pd
import numpy as np

data = {"grammer":['python','c','java','go',np.NaN,'SQL','PHP','Python'], "score":[1.0, 2.0, np.NaN, 4.0, 5.0, 6.0, 7.0, 10.0]}
df = pd.DataFrame(data)
print(df)

输出结果为：

  grammer  score
0  python    1.0
1       c    2.0
2    java    NaN
3      go    4.0
4     NaN    5.0
5     SQL    6.0
6     PHP    7.0
7  Python   10.0

(1)将下面的字典创建为DataFrame<br>data = {"grammer":["Python","C","Java","GO",np.nan,"SQL","PHP","Python"]

下面是将字典创建为DataFrame的代码：

import pandas as pd
import numpy as np

data = {"grammer":['Python', 'C', 'Java', 'GO', np.nan, 'SQL', 'PHP', 'Python'], 
        "score":[1.0, 2.0, np.nan, 4.0, 5.0, 6.0, 7.0,10.0]}
df = pd.DataFrame(data)
print(df)

输出结果为：

  grammer  score
0  Python    1.0
1       C    2.0
2    Java    NaN
3      GO    4.0
4     NaN    5.0
5     SQL    6.0
6     PHP    7.0
7  Python   10.0