Question

我正在使用pandas从python文本文件中读取数据。文本文件中没有为数据分配标题值（列名）。我想将数据重塑为可读的形式。我面临的问题是可变的列长例如，在我的文本文件中，

    1,2,3,4,5,Hello,7,8
    1,2,3,4,5,7,8,
    1,2,3,4,5,7,8,
    1,2,3,4,5,Hello,7,8,

现在，当我创建数据框时，我想确保在第二行而不是Hello中写入“ NAN”，因为该列的值不存在。最后，给出列名并重新排列数据框后将看起来像这样。

    1,2,3,4,5,Hello,7,8
    1,2,3,4,5,"NA,"7,8,
    1,2,3,4,5,"NA",7,8,
    1,2,3,4,5,Hello,7,8,

Answer 1

回答更新的问题，以及针对这种情况的通用解决方案。

focus_col_idx = 5   # The column where you want to bring NaN in expected output
last_idx = df.shape[1] - 1

# Fetching the index of rows which have None in last column 
idx = df[df[last_idx].isnull()].index

# Shifting the column values for those rows with index idx
df.iloc[idx,focus_col_idx+1:] = df.iloc[idx,focus_col_idx:last_idx].values

# Putting NaN for second column where row index is idx
df.iloc[idx,focus_col_idx] = np.NaN

df


+---+----+---+---+---+---+-------+---+-----+
|   |  0 | 1 | 2 | 3 | 4 |   5   | 6 |  7  |
+---+----+---+---+---+---+-------+---+-----+
| 0 |  1 | 2 | 3 | 4 | 5 | Hello | 7 | 8.0 |
| 1 |  1 | 2 | 3 | 4 | 5 | NaN   | 7 | 8.0 |
| 2 |  1 | 2 | 3 | 4 | 5 | NaN   | 7 | 8.0 |
| 3 |  1 | 2 | 3 | 4 | 5 | Hello | 7 | 8.0 |
+---+----+---+---+---+---+-------+---+-----+

回答以前的数据

假设只有一列缺少值（例如，根据您以前的数据说第二列）。这是一个快速的解决方法-

df = pd.read_table('SO.txt',sep='\,', header=None)
df

+---+---+---+---+---+------+
|   | 0 | 1 | 2 | 3 |  4   |
+---+---+---+---+---+------+
| 0 | A | B | C | D | E    |
| 1 | A | C | D | E | None |
+---+---+---+---+---+------+


# Fetching the index of rows which have None in last column 
idx = df[df[4].isnull()].index
idx
# Int64Index([1], dtype='int64')

# Shifting the column values for those rows with index idx
df.iloc[idx,2:] = df.iloc[idx,1:4].values
df

+---+---+---+---+---+---+
|   | 0 | 1 | 2 | 3 | 4 |
+---+---+---+---+---+---+
| 0 | A | B | C | D | E |
| 1 | A | C | C | D | E |        # <- Notice the shifting.
+---+---+---+---+---+---+


# Putting NaN for second column where row index is idx
df.iloc[idx,1] = np.NaN

# Final output
df
+---+---+-----+---+---+---+
|   | 0 |  1  | 2 | 3 | 4 |
+---+---+-----+---+---+---+
| 0 | A | B   | C | D | E |
| 1 | A | NaN | C | D | E |
+---+---+-----+---+---+---+

从具有可变列数

1 个答案: