迭代創建的CSV文件，通過一系列的熊貓

Question

我有一個數據幀，df它看起來像這樣：

Site Roadname Count id Count_norm 
9 A316 Twickenham Rd, Richmond 1474 9SOUTHBOUND 1428 
9 A316 Twickenham Rd, Richmond 1375 9SOUTHBOUND 1329 
9 A316 Twickenham Rd, Richmond 1052 9SOUTHBOUND 1006 
9 A316 Twickenham Rd, Richmond 986  9SOUTHBOUND 940 
9 A316 Twickenham Rd, Richmond 1071 9SOUTHBOUND 1025 
9 A316 Twickenham Rd, Richmond 1206 9SOUTHBOUND 1160 
9 A316 Twickenham Rd, Richmond 1474 9NORTHBOUND 1428 
9 A316 Twickenham Rd, Richmond 1375 9NORTHBOUND 1329 
9 A316 Twickenham Rd, Richmond 1052 9NORTHBOUND 1006 
9 A316 Twickenham Rd, Richmond 986  9NORTHBOUND 940 
9 A316 Twickenham Rd, Richmond 1071 9NORTHBOUND 1025 
9 A316 Twickenham Rd, Richmond 1206 9NORTHBOUND 1160 

我可以通過一系列創建單獨的CSV的：

11N_series = results[results.id == "11NORTHBOUND"] 
11N_series.to_csv('./11NORTHBOUND.csv') 

然而，這需要我定義每個系列的名稱（id）

如何迭代通過df數據框並按導出csv？

我可以看到每個ID的數量和名稱：

[in] id_count = results.groupby(["id"]).size() 
print(id_count) 

[out] 
id 
11NORTHBOUND 467 
11SOUTHBOUND 467 
15NORTHBOUND 467 

Answer 1

這裏是一個可能的方式做到這一點：

import pandas as pd 
from StringIO import StringIO 

st = """ 
Site|Roadname|Count|id|Count_norm 
9|A316 Twickenham Rd, Richmond|1474|9SOUTHBOUND|1428 
9|A316 Twickenham Rd, Richmond|1375|9SOUTHBOUND|1329 
9|A316 Twickenham Rd, Richmond|1052|9SOUTHBOUND|1006 
9|A316 Twickenham Rd, Richmond|986|9SOUTHBOUND|940 
9|A316 Twickenham Rd, Richmond|1071|9SOUTHBOUND|1025 
9|A316 Twickenham Rd, Richmond|1206|9SOUTHBOUND|1160 
9|A316 Twickenham Rd, Richmond|1474|9NORTHBOUND|1428 
9|A316 Twickenham Rd, Richmond|1375|9NORTHBOUND|1329 
9|A316 Twickenham Rd, Richmond|1052|9NORTHBOUND|1006 
9|A316 Twickenham Rd, Richmond|986|9NORTHBOUND|940 
9|A316 Twickenham Rd, Richmond|1071|9NORTHBOUND|1025 
9|A316 Twickenham Rd, Richmond|1206|9NORTHBOUND|1160 
""" 

data = pd.read_csv(StringIO(st), delimiter="|", error_bad_lines=False) 

#get a list of unique ids 
ids = pd.unique(data["id"].values.ravel()) 

grouped_data = data.groupby("id") 
for id in ids: 
    #get the dataframe for the current id 
    df = grouped_data.get_group(id) 
    #export current id's dataframe to a csv file with its name 
    df.to_csv(str(id)+".csv", sep="|", index=False)