今天学习几个查看dataframe的方法。首先,先生成一个dataframe:
df=pro.daily(ts_code='000001.SZ', start_date='20231120', end_date='20231123')
df
结果为:
ts_code |
trade_date |
crncy_code |
pre_close |
open |
high |
low |
close |
change |
pct_chg |
volume |
amount |
adj_pre_close |
adj_open |
adj_high |
adj_low |
adj_close |
adj_factor |
avg_price |
trade_status |
|
0 |
000001.SZ |
20231123 |
CNY |
10.16 |
10.15 |
10.16 |
10.07 |
10.15 |
-0.01 |
-0.0984 |
846655.87 |
855904.312 |
1185.8012 |
1184.6340 |
1185.8012 |
1175.2970 |
1184.6340 |
116.712713 |
10.1092 |
交易 |
1 |
000001.SZ |
20231122 |
CNY |
10.28 |
10.26 |
10.31 |
10.14 |
10.16 |
-0.12 |
-1.1673 |
737489.51 |
753064.758 |
1199.8067 |
1197.4724 |
1203.3081 |
1183.4669 |
1185.8012 |
116.712713 |
10.2112 |
交易 |
2 |
000001.SZ |
20231121 |
CNY |
10.19 |
10.23 |
10.35 |
10.22 |
10.28 |
0.09 |
0.8832 |
1041165.73 |
1072311.504 |
1189.3025 |
1193.9711 |
1207.9766 |
1192.8039 |
1199.8067 |
116.712713 |
10.2991 |
交易 |
3 |
000001.SZ |
20231120 |
CNY |
10.15 |
10.15 |
10.22 |
10.10 |
10.19 |
0.04 |
0.3941 |
639528.31 |
650077.370 |
1184.6340 |
1184.6340 |
1192.8039 |
1178.7984 |
1189.3025 |
116.712713 |
10.1650 |
交易 |
这是一个4行20列的表格。
1、df.shape,用来查看表格的行列数。
df.shape
返回(4行20列):
(4, 20)
2、df.values,以二维数组的形式返回数据,不包含行标和列标。
df.values
返回:
array([['000001.SZ', '20231123', 'CNY', 10.16, 10.15, 10.16, 10.07,
10.15, -0.01, -0.0984, 846655.87, 855904.312, 1185.8012,
1184.634, 1185.8012, 1175.297, 1184.634, 116.712713, 10.1092,
'交易'],
['000001.SZ', '20231122', 'CNY', 10.28, 10.26, 10.31, 10.14,
10.16, -0.12, -1.1673, 737489.51, 753064.758, 1199.8067,
1197.4724, 1203.3081, 1183.4669, 1185.8012, 116.712713, 10.2112,
'交易'],
['000001.SZ', '20231121', 'CNY', 10.19, 10.23, 10.35, 10.22,
10.28, 0.09, 0.8832, 1041165.73, 1072311.504, 1189.3025,
1193.9711, 1207.9766, 1192.8039, 1199.8067, 116.712713, 10.2991,
'交易'],
['000001.SZ', '20231120', 'CNY', 10.15, 10.15, 10.22, 10.1, 10.19,
0.04, 0.3941, 639528.31, 650077.37, 1184.634, 1184.634,
1192.8039, 1178.7984, 1189.3025, 116.712713, 10.165, '交易']],
dtype=object)
3、df.columns,返回各列的名称。
df.columns
返回:
Index(['ts_code', 'trade_date', 'crncy_code', 'pre_close', 'open', 'high',
'low', 'close', 'change', 'pct_chg', 'volume', 'amount',
'adj_pre_close', 'adj_open', 'adj_high', 'adj_low', 'adj_close',
'adj_factor', 'avg_price', 'trade_status'],
dtype='object')
4、df.head(),返回从第一条开始的条数,条数填在括号里,如果不填,则返回5条。df.tail(),跟df.head()相同用法,不同之处是返回的条数从最后一条往前数。
print(f'获取前3行:\n{df.head(3)}\n')
print(f'获取后2行:\n{df.tail(2)}')
返回:
获取前3行:
ts_code trade_date crncy_code pre_close open high low close \
0 000001.SZ 20231123 CNY 10.16 10.15 10.16 10.07 10.15
1 000001.SZ 20231122 CNY 10.28 10.26 10.31 10.14 10.16
2 000001.SZ 20231121 CNY 10.19 10.23 10.35 10.22 10.28
change pct_chg volume amount adj_pre_close adj_open \
0 -0.01 -0.0984 846655.87 855904.312 1185.8012 1184.6340
1 -0.12 -1.1673 737489.51 753064.758 1199.8067 1197.4724
2 0.09 0.8832 1041165.73 1072311.504 1189.3025 1193.9711
adj_high adj_low adj_close adj_factor avg_price trade_status
0 1185.8012 1175.2970 1184.6340 116.712713 10.1092 交易
1 1203.3081 1183.4669 1185.8012 116.712713 10.2112 交易
2 1207.9766 1192.8039 1199.8067 116.712713 10.2991 交易
获取后2行:
ts_code trade_date crncy_code pre_close open high low close \
2 000001.SZ 20231121 CNY 10.19 10.23 10.35 10.22 10.28
3 000001.SZ 20231120 CNY 10.15 10.15 10.22 10.10 10.19
change pct_chg volume amount adj_pre_close adj_open \
2 0.09 0.8832 1041165.73 1072311.504 1189.3025 1193.9711
3 0.04 0.3941 639528.31 650077.370 1184.6340 1184.6340
adj_high adj_low adj_close adj_factor avg_price trade_status
2 1207.9766 1192.8039 1199.8067 116.712713 10.2991 交易
3 1192.8039 1178.7984 1189.3025 116.712713 10.1650 交易
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