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分析调仓对收益的影响

未完成
中级参考 代码结构已给出，请填写 ____ 处 
def solve():
    from pyodide.http import open_url
    from io import StringIO
    import pandas as pd
    csv_data = open_url(____).read()
    df = pd.read_csv(StringIO(____))
    result = df['____'].value_counts()
    for val, count in result.items():
        print(____)

示例

输入
solve()
期望输出
RB0001: 1
RB0002: 1
RB0003: 1
RB0004: 1
RB0005: 1
RB0006: 1
RB0007: 1
RB0008: 1
RB0009: 1
RB0010: 1
RB0011: 1
RB0012: 1
RB0013: 1
RB0014: 1
RB0015: 1
RB0016: 1
RB0017: 1
RB0018: 1
RB0019: 1
RB0020: 1
RB0021: 1
RB0022: 1
RB0023: 1
RB0024: 1
RB0025: 1
RB0026: 1
RB0027: 1
RB0028: 1
RB0029: 1
RB0030: 1
RB0031: 1
RB0032: 1
RB0033: 1
RB0034: 1
RB0035: 1
RB0036: 1
RB0037: 1
RB0038: 1
RB0039: 1
RB0040: 1
RB0041: 1
RB0042: 1
RB0043: 1
RB0044: 1
RB0045: 1
RB0046: 1
RB0047: 1
RB0048: 1
RB0049: 1
RB0050: 1
RB0051: 1
RB0052: 1
RB0053: 1
RB0054: 1
RB0055: 1
RB0056: 1
RB0057: 1
RB0058: 1
RB0059: 1
RB0060: 1
RB0061: 1
RB0062: 1
RB0063: 1
RB0064: 1
RB0065: 1
RB0066: 1
RB0067: 1
RB0068: 1
RB0069: 1
RB0070: 1
RB0071: 1
RB0072: 1
RB0073: 1
RB0074: 1
RB0075: 1
RB0076: 1
RB0077: 1
RB0078: 1
RB0079: 1
RB0080: 1
RB0081: 1
RB0082: 1
RB0083: 1
RB0084: 1
RB0085: 1
RB0086: 1
RB0087: 1
RB0088: 1
RB0089: 1
RB0090: 1
RB0091: 1
RB0092: 1
RB0093: 1
RB0094: 1
RB0095: 1
RB0096: 1
RB0097: 1
RB0098: 1
RB0099: 1
RB0100: 1
RB0101: 1
RB0102: 1
RB0103: 1
RB0104: 1
RB0105: 1
RB0106: 1
RB0107: 1
RB0108: 1
RB0109: 1
RB0110: 1
RB0111: 1
RB0112: 1
RB0113: 1
RB0114: 1
RB0115: 1
RB0116: 1
RB0117: 1
RB0118: 1
RB0119: 1
RB0120: 1
RB0121: 1
RB0122: 1
RB0123: 1
RB0124: 1
RB0125: 1
RB0126: 1
RB0127: 1
RB0128: 1
RB0129: 1
RB0130: 1
RB0131: 1
RB0132: 1
RB0133: 1
RB0134: 1
RB0135: 1
RB0136: 1
RB0137: 1
RB0138: 1
RB0139: 1
RB0140: 1
RB0141: 1
RB0142: 1
RB0143: 1
RB0144: 1
RB0145: 1
RB0146: 1
RB0147: 1
RB0148: 1
RB0149: 1
RB0150: 1
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