如何输入cvs并获取最小值和最大值python答案

【问题标题】：How to input cvs and get min and max values python如何输入cvs并获取最小值和最大值python
【发布时间】：2021-03-17 05:56:30
【问题描述】：

将相同的 hsv_2020_climo_data.csv 文件读入 Pandas DataFrame，并将 Date 列作为索引（类似于前面的示例）。用格式化的打印语句回答下列问题。每列的数据类型是什么？（即“MaxTemperature”dtype 是 int64）全年最高最高温度是多少？全年最低气温是多少？ 2020 年我们总共下了多少雨？（提示您需要先处理“Trace”值）绘制带有标签和标题的最高温度、最低温度和平均温度的图。

以下数据

Date     MaxTemperature  MinTemperature  AvgTemperature  Precipitation   Snowfall    SnowDepth
2020-01-01  53  31  42.0    0.00    0.0 0
2020-01-02  54  45  49.5    3.42    0.0 0
2020-01-03  59  53  56.0    0.32    0.0 0
2020-01-04  56  31  43.5    0.08    0.0 0
2020-01-05  55  29  42.0    0.00    0.0 0
2020-01-06  60  35  47.5    0.03    0.0 0
2020-01-07  55  35  45.0     T  0.0 0
2020-01-08  61  30  45.5    0.00    0.0 0
2020-01-09  60  36  48.0    0.00    0.0 0
2020-01-10  65  58  61.5     T  0.0 0
2020-01-11  72  50  61.0    1.08    0.0 0
2020-01-12  59  46  52.5    0.00    0.0 0
2020-01-13  62  43  52.5    0.08    0.0 0
2020-01-14  64  60  62.0    0.96    0.0 0
2020-01-15  67  60  63.5    0.61    0.0 0
2020-01-16  60  42  51.0    0.03    0.0 0
2020-01-17  59  40  49.5    0.00    0.0 0
2020-01-18  57  45  51.0    0.17    0.0 0
2020-01-19  45  27  36.0    0.00    0.0 0
2020-01-20  28  22  25.0     T   T  0
2020-01-21  37  23  30.0    0.00    0.0 0
2020-01-22  46  20  33.0    0.00    0.0 0
2020-01-23  47  39  43.0    0.72    0.0 0
2020-01-24  54  40  47.0    0.19    0.0 0
2020-01-25  41  33  37.0     T  0.0 0
2020-01-26  49  29  39.0    0.03    0.0 0
2020-01-27  58  37  47.5    0.01    0.0 0
2020-01-28  60  31  45.5    0.00    0.0 0
2020-01-29  50  44  47.0    0.03    0.0 0
2020-01-30  60  37  48.5    0.00    0.0 0
2020-01-31  52  45  48.5     T  0.0 0
2020-02-01  50  37  43.5    0.06    0.0 0
2020-02-02  68  31  49.5    0.00    0.0 0
2020-02-03  71  40  55.5     T  0.0 0
2020-02-04  67  55  61.0    0.18    0.0 0
2020-02-05  68  62  65.0    1.16    0.0 0
2020-02-06  64  36  50.0    1.49    0.0 0
2020-02-07  41  33  37.0     T   T  0
2020-02-08  53  32  42.5    0.10     T  0
2020-02-09  61  33  47.0     T  0.0 0
2020-02-10  57  49  53.0    1.78    0.0 0
2020-02-11  66  45  55.5    1.12    0.0 0
2020-02-12  70  44  57.0    1.31    0.0 0
2020-02-13  60  36  48.0    0.38    0.0 0
2020-02-14  41  26  33.5    0.00    0.0 0
2020-02-15  54  22  38.0    0.00    0.0 0
2020-02-16  58  42  50.0    0.00    0.0 0
2020-02-17  56  38  47.0    0.00    0.0 0
2020-02-18  62  46  54.0    1.32    0.0 0
2020-02-19  52  43  47.5     T  0.0 0
2020-02-20  47  33  40.0    0.85     T  0
2020-02-21  44  26  35.0    0.00    0.0 0
2020-02-22  56  24  40.0    0.00    0.0 0
2020-02-23  53  34  43.5    0.01    0.0 0
2020-02-24  55  44  49.5    0.62    0.0 0
2020-02-25  62  45  53.5    0.00    0.0 0
2020-02-26  48  36  42.0    0.04     T  0
2020-02-27  46  31  38.5     T   T  0
2020-02-28  51  34  42.5     T  0.0 0
2020-02-29  55  36  45.5    0.00    0.0 0
2020-03-01  66  34  50.0    0.00    0.0 0
2020-03-02  60  52  56.0    0.44    0.0 0
2020-03-03  69  55  62.0    0.33    0.0 0
2020-03-04  60  51  55.5    0.04    0.0 0
2020-03-05  59  42  50.5    0.15    0.0 0
2020-03-06  56  37  46.5    0.00    0.0 0
2020-03-07  58  30  44.0    0.00    0.0 0
2020-03-08  65  35  50.0    0.00    0.0 0
2020-03-09  68  45  56.5     T  0.0 0
2020-03-10  70  56  63.0    0.27    0.0 0
2020-03-11  66  51  58.5    0.12    0.0 0
2020-03-12  76  57  66.5    0.26    0.0 0
2020-03-13  67  54  60.5    0.14    0.0 0
2020-03-14  74  50  62.0    0.56    0.0 0
2020-03-15  61  44  52.5    1.07    0.0 0
2020-03-16  59  44  51.5    0.02    0.0 0
2020-03-17  74  53  63.5    0.24    0.0 0
2020-03-18  77  52  64.5    0.00    0.0 0
2020-03-19  78  64  71.0     T  0.0 0
2020-03-20  72  60  66.0    1.11    0.0 0
2020-03-21  59  43  51.0    0.01    0.0 0
2020-03-22  66  43  54.5    0.07    0.0 0
2020-03-23  64  57  60.5    1.80    0.0 0
2020-03-24  76  57  66.5    2.96    0.0 0
2020-03-25  66  51  58.5    0.00    0.0 0
2020-03-26  81  47  64.0    0.00    0.0 0
2020-03-27  85  63  74.0    0.00    0.0 0
2020-03-28  82  66  74.0    0.00    0.0 0
2020-03-29  75  53  64.0    0.41    0.0 0
2020-03-30  70  52  61.0    0.02    0.0 0
2020-03-31  56  43  49.5    0.65    0.0 0
2020-04-01  62  39  50.5    0.00    0.0 0
2020-04-02  70  38  54.0    0.00    0.0 0
2020-04-03  75  42  58.5    0.00    0.0 0
2020-04-04  78  54  66.0    0.00    0.0 0
2020-04-05  81  54  67.5    0.00    0.0 0
2020-04-06  83  52  67.5    0.00    0.0 0
2020-04-07  74  62  68.0    0.00    0.0 0
2020-04-08  80  63  71.5    0.24    0.0 0
2020-04-09  71  57  64.0    0.32    0.0 0
2020-04-10  60  40  50.0    0.00    0.0 0
2020-04-11  71  37  54.0    0.00    0.0 0
2020-04-12  66  54  60.0    3.02    0.0 0
2020-04-13  66  42  54.0     T  0.0 0
2020-04-14  59  39  49.0    0.00    0.0 0
2020-04-15  61  34  47.5    0.00    0.0 0
2020-04-16  69  36  52.5    0.00    0.0 0
2020-04-17  76  45  60.5    0.07    0.0 0
2020-04-18  62  45  53.5    0.21    0.0 0
2020-04-19  63  46  54.5    1.41    0.0 0
2020-04-20  72  51  61.5    0.11    0.0 0
2020-04-21  76  50  63.0    0.00    0.0 0
2020-04-22  68  42  55.0    0.29    0.0 0
2020-04-23  70  54  62.0    0.92    0.0 0
2020-04-24  73  56  64.5    0.01    0.0 0
2020-04-25  74  53  63.5    0.21    0.0 0
2020-04-26  61  41  51.0    0.00    0.0 0
2020-04-27  72  38  55.0    0.00    0.0 0
2020-04-28  77  53  65.0     T  0.0 0
2020-04-29  72  53  62.5    0.13    0.0 0
2020-04-30  71  48  59.5     T  0.0 0
2020-05-01  76  43  59.5    0.00    0.0 0
2020-05-02  83  51  67.0    0.00    0.0 0
2020-05-03  85  58  71.5    0.00    0.0 0
2020-05-04  84  60  72.0     T  0.0 0
2020-05-05  76  56  66.0     T  0.0 0
2020-05-06  65  44  54.5    0.00    0.0 0
2020-05-07  71  39  55.0    0.00    0.0 0
2020-05-08  61  48  54.5    0.86    0.0 0
2020-05-09  64  40  52.0    0.00    0.0 0
2020-05-10  73  39  56.0    0.00    0.0 0
2020-05-11  68  43  55.5    0.00    0.0 0
2020-05-12  66  48  57.0     T  0.0 0
2020-05-13  79  55  67.0    0.05    0.0 0
2020-05-14  85  61  73.0    0.00    0.0 0
2020-05-15  84  67  75.5    0.00    0.0 0
2020-05-16  86  62  74.0    0.00    0.0 0
2020-05-17  79  65  72.0    0.23    0.0 0
2020-05-18  82  60  71.0     T  0.0 0
2020-05-19  71  54  62.5     T  0.0 0
2020-05-20  77  54  65.5    0.25    0.0 0
2020-05-21  79  57  68.0    0.00    0.0 0
2020-05-22  82  63  72.5    1.52    0.0 0
2020-05-23  86  64  75.0    0.28    0.0 0
2020-05-24  88  65  76.5     T  0.0 0
2020-05-25  88  67  77.5    0.00    0.0 0
2020-05-26  76  67  71.5    0.31    0.0 0
2020-05-27  79  61  70.0    0.74    0.0 0
2020-05-28  83  62  72.5    0.21    0.0 0
2020-05-29  83  64  73.5    0.18    0.0 0
2020-05-30  84  63  73.5    0.00    0.0 0
2020-05-31  83  59  71.0    0.00    0.0 0
2020-06-01  85  53  69.0    0.00    0.0 0
2020-06-02  89  67  78.0    0.00    0.0 0
2020-06-03  88  71  79.5    0.06    0.0 0
2020-06-04  87  68  77.5     T  0.0 0
2020-06-05  90  69  79.5    0.41    0.0 0
2020-06-06  91  68  79.5    0.00    0.0 0
2020-06-07  91  71  81.0    0.00    0.0 0
2020-06-08  84  75  79.5    0.43    0.0 0
2020-06-09  87  75  81.0    0.11    0.0 0
2020-06-10  92  65  78.5    0.00    0.0 0
2020-06-11  85  61  73.0    0.00    0.0 0
2020-06-12  88  61  74.5    0.00    0.0 0
2020-06-13  90  58  74.0    0.00    0.0 0
2020-06-14  92  62  77.0    0.00    0.0 0
2020-06-15  83  61  72.0    0.00    0.0 0
2020-06-16  81  60  70.5    0.00    0.0 0
2020-06-17  80  63  71.5    0.00    0.0 0
2020-06-18  85  61  73.0    0.00    0.0 0
2020-06-19  91  64  77.5    0.00    0.0 0
2020-06-20  94  66  80.0    0.00    0.0 0
2020-06-21  88  69  78.5    0.14    0.0 0
2020-06-22  88  68  78.0    0.14    0.0 0
2020-06-23  87  70  78.5    0.25    0.0 0
2020-06-24  75  68  71.5    0.70    0.0 0
2020-06-25  85  70  77.5    0.00    0.0 0
2020-06-26  75  68  71.5    0.15    0.0 0
2020-06-27  82  68  75.0    0.30    0.0 0
2020-06-28  90  73  81.5    0.25    0.0 0
2020-06-29  90  71  80.5    0.01    0.0 0
2020-06-30  88  70  79.0    0.84    0.0 0
2020-07-01  82  68  75.0    0.73    0.0 0
2020-07-02  89  68  78.5    0.00    0.0 0
2020-07-03  94  71  82.5    0.00    0.0 0
2020-07-04  92  71  81.5    0.00    0.0 0
2020-07-05  93  71  82.0    0.47    0.0 0
2020-07-06  88  71  79.5    0.00    0.0 0
2020-07-07  90  73  81.5    0.07    0.0 0
2020-07-08  87  73  80.0     T  0.0 0
2020-07-09  90  71  80.5    0.00    0.0 0
2020-07-10  92  73  82.5    0.00    0.0 0
2020-07-11  92  67  79.5    0.00    0.0 0
2020-07-12  82  68  75.0    1.38    0.0 0
2020-07-13  89  69  79.0    0.00    0.0 0
2020-07-14  91  70  80.5    0.00    0.0 0
2020-07-15  93  70  81.5    0.00    0.0 0
2020-07-16  91  70  80.5    0.00    0.0 0
2020-07-17  94  73  83.5    0.00    0.0 0
2020-07-18  95  73  84.0    0.00    0.0 0
2020-07-19  95  73  84.0    0.00    0.0 0
2020-07-20  95  73  84.0    0.00    0.0 0
2020-07-21  94  74  84.0     T  0.0 0
2020-07-22  92  73  82.5    0.19    0.0 0
2020-07-23  92  71  81.5    0.00    0.0 0
2020-07-24  90  73  81.5    0.00    0.0 0
2020-07-25  94  72  83.0    0.07    0.0 0
2020-07-26  94  71  82.5    0.00    0.0 0
2020-07-27  91  73  82.0     T  0.0 0
2020-07-28  90  72  81.0     T  0.0 0
2020-07-29  92  73  82.5    0.02    0.0 0
2020-07-30  90  74  82.0    0.14    0.0 0
2020-07-31  92  74  83.0    0.25    0.0 0
2020-08-01  87  70  78.5     T  0.0 0
2020-08-02  86  66  76.0    0.00    0.0 0
2020-08-03  91  67  79.0    0.00    0.0 0
2020-08-04  90  70  80.0    0.01    0.0 0
2020-08-05  92  68  80.0    0.00    0.0 0
2020-08-06  92  71  81.5    0.00    0.0 0
2020-08-07  94  69  81.5    0.00    0.0 0
2020-08-08  97  68  82.5    0.00    0.0 0
2020-08-09  96  71  83.5    0.00    0.0 0
2020-08-10  98  74  86.0    0.00    0.0 0
2020-08-11  95  73  84.0    0.49    0.0 0
2020-08-12  93  74  83.5    0.01    0.0 0
2020-08-13  94  71  82.5     T  0.0 0
2020-08-14  90  74  82.0     T  0.0 0
2020-08-15  92  71  81.5    0.00    0.0 0
2020-08-16  93  67  80.0     T  0.0 0
2020-08-17  91  67  79.0    0.00    0.0 0
2020-08-18  93  64  78.5    0.24    0.0 0
2020-08-19  91  68  79.5    1.24    0.0 0
2020-08-20  87  67  77.0     T  0.0 0
2020-08-21  82  68  75.0    0.10    0.0 0
2020-08-22  85  64  74.5    0.00    0.0 0
2020-08-23  88  68  78.0    0.00    0.0 0
2020-08-24  88  72  80.0     T  0.0 0
2020-08-25  82  72  77.0    0.15    0.0 0
2020-08-26  85  70  77.5    1.83    0.0 0
2020-08-27  91  75  83.0    0.22    0.0 0
2020-08-28  86  72  79.0    0.92    0.0 0
2020-08-29  90  74  82.0    0.02    0.0 0
2020-08-30  91  71  81.0    0.23    0.0 0
2020-08-31  87  71  79.0    0.94    0.0 0
2020-09-01  89  71  80.0    0.05    0.0 0
2020-09-02  89  74  81.5    0.00    0.0 0
2020-09-03  89  73  81.0    0.00    0.0 0
2020-09-04  90  67  78.5     T  0.0 0
2020-09-05  88  59  73.5    0.00    0.0 0
2020-09-06  86  57  71.5    0.00    0.0 0
2020-09-07  86  60  73.0    0.00    0.0 0
2020-09-08  87  64  75.5    0.00    0.0 0
2020-09-09  88  65  76.5    0.00    0.0 0
2020-09-10  90  66  78.0    0.00    0.0 0
2020-09-11  93  68  80.5    0.00    0.0 0
2020-09-12  90  73  81.5    0.01    0.0 0
2020-09-13  91  71  81.0     T  0.0 0
2020-09-14  90  69  79.5    0.00    0.0 0
2020-09-15  83  69  76.0    0.00    0.0 0
2020-09-16  74  68  71.0    0.12    0.0 0
2020-09-17  87  70  78.5    0.00    0.0 0
2020-09-18  79  61  70.0    0.00    0.0 0
2020-09-19  76  59  67.5    0.00    0.0 0
2020-09-20  81  58  69.5    0.00    0.0 0
2020-09-21  76  53  64.5    0.00    0.0 0
2020-09-22  75  51  63.0     T  0.0 0
2020-09-23  71  53  62.0    0.79    0.0 0
2020-09-24  66  55  60.5    2.65    0.0 0
2020-09-25  73  64  68.5     T  0.0 0
2020-09-26  76  62  69.0    0.00    0.0 0
2020-09-27  83  61  72.0    0.00    0.0 0
2020-09-28  82  56  69.0    0.42    0.0 0
2020-09-29  70  49  59.5    0.00    0.0 0
2020-09-30  77  47  62.0    0.00    0.0 0
2020-10-01  76  51  63.5    0.00    0.0 0
2020-10-02  69  44  56.5    0.00    0.0 0
2020-10-03  71  40  55.5    0.00    0.0 0
2020-10-04  76  50  63.0    0.00    0.0 0
2020-10-05  76  48  62.0    0.00    0.0 0
2020-10-06  80  48  64.0    0.00    0.0 0
2020-10-07  82  52  67.0    0.00    0.0 0
2020-10-08  82  49  65.5    0.00    0.0 0
2020-10-09  73  63  68.0    0.47    0.0 0
2020-10-10  74  64  69.0    1.35    0.0 0
2020-10-11  75  68  71.5    0.23    0.0 0
2020-10-12  80  64  72.0    0.00    0.0 0
2020-10-13  76  52  64.0    0.00    0.0 0
2020-10-14  82  45  63.5    0.00    0.0 0
2020-10-15  80  54  67.0    0.00    0.0 0
2020-10-16  66  39  52.5    0.01    0.0 0
2020-10-17  68  37  52.5    0.00    0.0 0
2020-10-18  76  50  63.0    0.00    0.0 0
2020-10-19  80  56  68.0    0.00    0.0 0
2020-10-20  81  59  70.0    0.00    0.0 0
2020-10-21  81  58  69.5    0.00    0.0 0
2020-10-22  83  62  72.5    0.00    0.0 0
2020-10-23  83  63  73.0    0.03    0.0 0
2020-10-24  66  55  60.5    0.44    0.0 0
2020-10-25  69  55  62.0    0.00    0.0 0
2020-10-26  75  58  66.5    0.00    0.0 0
2020-10-27  75  58  66.5     T  0.0 0
2020-10-28  74  69  71.5    2.87    0.0 0
2020-10-29  72  48  60.0    0.58    0.0 0
2020-10-30  57  42  49.5    0.00    0.0 0
2020-10-31  68  40  54.0    0.00    0.0 0
2020-11-01  68  43  55.5    0.00    0.0 0
2020-11-02  57  33  45.0    0.00    0.0 0
2020-11-03  66  34  50.0    0.00    0.0 0
2020-11-04  71  39  55.0    0.00    0.0 0
2020-11-05  70  44  57.0    0.00    0.0 0
2020-11-06  76  46  61.0    0.00    0.0 0
2020-11-07  75  48  61.5     T  0.0 0
2020-11-08  79  59  69.0    0.00    0.0 0
2020-11-09  78  62  70.0    0.00    0.0 0
2020-11-10  74  65  69.5     T  0.0 0
2020-11-11  77  58  67.5    0.04    0.0 0
2020-11-12  68  44  56.0    0.00    0.0 0
2020-11-13  71  42  56.5    0.00    0.0 0
2020-11-14  73  41  57.0    0.00    0.0 0
2020-11-15  69  40  54.5    0.02    0.0 0
2020-11-16  63  32  47.5    0.00    0.0 0
2020-11-17  62  34  48.0    0.00    0.0 0
2020-11-18  64  31  47.5    0.00    0.0 0
2020-11-19  66  38  52.0    0.00    0.0 0
2020-11-20  72  40  56.0    0.00    0.0 0
2020-11-21  73  42  57.5    0.00    0.0 0
2020-11-22  69  46  57.5    0.02    0.0 0
2020-11-23  57  35  46.0    0.00    0.0 0
2020-11-24  65  32  48.5    0.00    0.0 0
2020-11-25  65  53  59.0    0.48    0.0 0
2020-11-26  62  40  51.0    0.00    0.0 0
2020-11-27  66  38  52.0    0.58    0.0 0
2020-11-28  57  41  49.0     T  0.0 0
2020-11-29  55  39  47.0    0.73    0.0 0
2020-11-30  44  30  37.0    0.08     T  0
2020-12-01  41  25  33.0    0.00    0.0 0
2020-12-02  52  20  36.0    0.00    0.0 0
2020-12-03  58  25  41.5    0.16    0.0 0
2020-12-04  48  35  41.5    0.82    0.0 0
2020-12-05  56  28  42.0    0.00    0.0 0
2020-12-06  59  30  44.5     T  0.0 0
2020-12-07  47  28  37.5    0.00    0.0 0
2020-12-08  49  25  37.0    0.00    0.0 0
2020-12-09  64  28  46.0    0.00    0.0 0
2020-12-10  71  35  53.0    0.00    0.0 0
2020-12-11  66  37  51.5    0.00    0.0 0
2020-12-12  63  46  54.5    0.30    0.0 0
2020-12-13  60  34  47.0    0.80    0.0 0
2020-12-14  44  35  39.5    0.81    0.0 0
2020-12-15  48  30  39.0     T  0.0 0
2020-12-16  50  35  42.5    0.26    0.0 0
2020-12-17  43  26  34.5    0.00    0.0 0
2020-12-18  50  23  36.5    0.00    0.0 0
2020-12-19  53  27  40.0    0.03    0.0 0
2020-12-20  51  40  45.5    0.16    0.0 0
2020-12-21  61  38  49.5    0.00    0.0 0
2020-12-22  60  31  45.5    0.00    0.0 0
2020-12-23  61  35  48.0    0.12    0.0 0
2020-12-24  52  28  40.0    1.13     T  0
2020-12-25  32  20  26.0    0.00    0.0 0
2020-12-26  50  18  34.0    0.00    0.0 0
2020-12-27  60  26  43.0    0.00    0.0 0
2020-12-28  57  37  47.0    0.00    0.0 0
2020-12-29  61  33  47.0    0.00    0.0 0
2020-12-30  69  41  55.0    0.00    0.0 0
2020-12-31  59  50  54.5    0.03    0.0 0

【问题讨论】：

上传 .csv 文件以便我可以访问它。

标签： python-3.x pandas

【解决方案1】：

首先，请注意某些列包含值“T”。要解决一些问题，您必须替换那些问题：

df = pd.read_csv(r"C:\users\....\DATA.csv", sep=";")
df.replace('T',0, inplace = True)

获取数据类型：

df.info()
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 366 entries, 0 to 365
Data columns (total 7 columns):
 #   Column          Non-Null Count  Dtype  
---  ------          --------------  -----  
 0   Date            366 non-null    object 
 1   MaxTemperature  366 non-null    int64  
 2   MinTemperature  366 non-null    int64  
 3   AvgTemperature  366 non-null    float64
 4   Precipitation   366 non-null    object 
 5   Snowfall        366 non-null    object 
 6   SnowDepth       366 non-null    int64  
dtypes: float64(1), int64(3), object(3)
memory usage: 20.1+ KB

要获得您询问的所有信息，您需要将object 值转换为float。它们是字符串，因为您使用“T”值而不是数字：

df['Precipitation'] = df.Precipitation.astype(float)
df['Snowfall'] = df.Snowfall.astype(float)
df['SnowDepth'] = df.SnowDepth.astype(float)

请注意

df.info()
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 366 entries, 0 to 365
Data columns (total 7 columns):
 #   Column          Non-Null Count  Dtype  
---  ------          --------------  -----  
 0   Date            366 non-null    object 
 1   MaxTemperature  366 non-null    int64  
 2   MinTemperature  366 non-null    int64  
 3   AvgTemperature  366 non-null    float64
 4   Precipitation   366 non-null    float64
 5   Snowfall        366 non-null    float64
 6   SnowDepth       366 non-null    float64
dtypes: float64(4), int64(2), object(1)
memory usage: 20.1+ KB

现在回答所有问题：

df.describe()

       MaxTemperature  MinTemperature  AvgTemperature  Precipitation  \
count      366.000000      366.000000      366.000000     366.000000   
mean        73.021858       52.229508       62.625683       0.192678   
std         14.496086       14.966696       14.317651       0.471406   
min         28.000000       18.000000       25.000000       0.000000   
25%         61.250000       40.000000       51.000000       0.000000   
50%         74.000000       53.000000       63.250000       0.000000   
75%         86.000000       67.000000       75.500000       0.140000   
max         98.000000       75.000000       86.000000       3.420000   

       Snowfall  SnowDepth  
count     366.0      366.0  
mean        0.0        0.0  
std         0.0        0.0  
min         0.0        0.0  
25%         0.0        0.0  
50%         0.0        0.0  
75%         0.0        0.0  
max         0.0        0.0

您有所有变量的最大值、最小值、...。

至于剧情

lines = df.plot.line()

【讨论】：