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<p>无法将Python dict转换为表,然后将数据导出到csv。在</p>
<pre><code>dict string: {"test_sheet": {"testheader": [{"2018-12-31": {"field1": 8482000000, "field2": 166731000000, "field3": 92128000000}}, {"2018-11-30": {"field1": 7579000000, "field2": 171652000000, "field3": 85967000000}}, {"2018-10-31": {"field1": 8053000000, "field2": 176130000000, "field3": 82718000000}}, {"2018-09-30": {"field1": 8544000000, "field2": 166258000000, "field3": 79239000000}}]}}
Format of table needed:
Report Name Date Field1 Field2 Field3
test_sheet testheader 31.12.2018 8482000000 166731000000 92128000000
test_sheet testheader 30.11.2018 7579000000 171652000000 85967000000
test_sheet testheader 31.10.2018 8053000000 176130000000 82718000000
test_sheet testheader 30.09.2018 8544000000 166258000000 79239000000
</code></pre>
<p>尝试使用read_json将dict转换为csv</p>
^{pr2}$
<p>但导出到csv后,所有数据都保存在第一行。在</p>
<p><strong>新的详细输入数据:</strong></p>
<pre><code>{"test_sheet": {"testheader": [ {"2018-12-31": {"field1": 8482000000, "field2": 166731000000, "field3": 92128000000}}, {"2018-11-30": {"field1": 7579000000, "field2": 171652000000, "field3": 85967000000, "field4": 6679000000, "field5": 159000000}}, {"2018-10-31": {"field1": 8053000000, "field2": 176130000000, "field3": 82718000000, "field4": 1218000000}}, {"2018-09-30": {"field1": 8544000000, "field2": 166258000000, "field3": 79239000000}}], "testheader1": [ {"2018-12-31": {"field1": 8482000000, "field2": 166731000000, "field3": 92128000000, "field4": 124000000}}, {"2018-11-30": {"field1": 7579000000, "field2": 171652000000, "field3": 85967000000, "field4": 44367000000, "field5": 582000000}}, {"2018-10-31": {"field1": 8053000000, "field2": 176130000000, "field3": 82718000000, "field4": 132500000, "field5": 15847000, "field6": 1982330000}}, {"2018-09-30": {"field1": 8544000000, "field2": 166258000000, "field3": 79239000000}}]}}
</code></pre>
<p><strong>此数据所需的输出格式:</strong></p>
<pre><code>Report Name Date FieldName FieldValue
test_sheet testheader 31.12.2018 Field1 8482000000
test_sheet testheader 31.12.2018 Field2 166731000000
test_sheet testheader 31.12.2018 Field3 92128000000
test_sheet testheader 30.11.2018 Field1 7579000000
test_sheet testheader 30.11.2018 Field2 171652000000
test_sheet testheader 30.11.2018 Field3 85967000000
test_sheet testheader 30.11.2018 Field4 6679000000
test_sheet testheader 30.11.2018 Field5 159000000
test_sheet testheader 31.10.2018 Field1 8053000000
test_sheet testheader 31.10.2018 Field2 176130000000
test_sheet testheader 31.10.2018 Field3 82718000000
test_sheet testheader 31.10.2018 Field4 1218000000
test_sheet testheader 30.09.2018 Field1 8544000000
test_sheet testheader 30.09.2018 Field2 166258000000
test_sheet testheader 30.09.2018 Field3 79239000000
test_sheet testheader1 31.12.2018 Field1 8482000000
test_sheet testheader1 31.12.2018 Field2 166731000000
test_sheet testheader1 31.12.2018 Field3 92128000000
test_sheet testheader1 31.12.2018 Field4 124000000
test_sheet testheader1 30.11.2018 Field1 7579000000
test_sheet testheader1 30.11.2018 Field2 171652000000
test_sheet testheader1 30.11.2018 Field3 85967000000
test_sheet testheader1 30.11.2018 Field4 44367000000
test_sheet testheader1 30.11.2018 Field5 582000000
test_sheet testheader1 31.10.2018 Field1 8053000000
test_sheet testheader1 31.10.2018 Field2 176130000000
test_sheet testheader1 31.10.2018 Field3 82718000000
test_sheet testheader1 31.10.2018 Field4 132500000
test_sheet testheader1 31.10.2018 Field5 15847000
test_sheet testheader1 31.10.2018 Field6 1982330000
test_sheet testheader1 30.09.2018 Field1 8544000000
test_sheet testheader1 30.09.2018 Field2 166258000000
test_sheet testheader1 30.09.2018 Field3 79239000000
</code></pre>